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Evaluation of Nutritional, Inflammatory and Fatty Acid Status in Patients with Gastric and Colorectal Cancers Receiving Chemotherapy
by
Denise Gabrielson
A thesis submitted in conformity with the requirements for the degree of Master of Science Department of Nutritional Sciences
Literature review .........................................................................................................................4
2.1 Gastrointestinal cancer .........................................................................................................4
2.1.1 Treatment in gastrointestinal cancer ........................................................................5
2.1.2 Standard medical nutrition therapy in oncology specific to gastrointestinal cancer and chemotherapy .........................................................................................6
2.2 Nutritional status and cancer ................................................................................................8
2.2.1 Nutritional status and cancer: screening and assessment .........................................8
2.2.1.1 Screening and assessment: body composition ...........................................9
2.2.2 Nutritional status and cancer: prevalence and identification of cancer-related malnutrition and cancer cachexia ...........................................................................11
2.3 Etiology and pathophysiology of cancer-related malnutrition and cachexia .....................14
2.3.1 Inflammation and cancer ........................................................................................14
2.3.1.1 Inflammation and gastrointestinal cancer: interleukin-6 and tumour necrosis factor alpha ................................................................................15
2.3.1.2 Inflammation and gastrointestinal cancer: C-reactive protein .................16
2.3.1.3 Inflammation and nutritional status in gastrointestinal cancer over time ..........................................................................................................16
2.3.2 Fatty acids in cancer ...............................................................................................17
2.3.2.1 Fatty acids: general background ..............................................................17
2.3.2.1.1Endogenous synthesis of long-chain polyunsaturated fatty acids .......... 18
v
2.3.2.1.2Long-chain polyunsaturated fatty acids and health ............................... 18
2.3.2.2 Role of fatty acids in cancer ....................................................................20
2.3.2.3 The influence of cancer on fatty acid status ............................................21
2.3.2.4 The influence of anti-cancer therapy on fatty acid status ........................22
2.3.3 The relationship between fatty acids and inflammation in cancer .........................23
2.3.3.1 Modulation of the inflammatory response with polyunsaturated fatty acids .........................................................................................................24
2.3.3.1.1n-3 supplementation in patients not receiving anti-cancer therapy ....... 25
2.3.3.1.2n-3 supplementation in patients receiving anti-cancer therapy ............. 27
5.1 Patient population ..............................................................................................................40
5.2 Patient characteristics prior to starting chemotherapy .......................................................40
5.3 Changes in nutritional, inflammatory and fatty acid status during chemotherapy – all patients ...............................................................................................................................44
5.3.1 Nutritional status ....................................................................................................44
5.3.2 Inflammatory status ...............................................................................................44
5.3.3 Fatty acid status ......................................................................................................44
5.4 Interrelationships between nutritional, inflammatory and fatty acid status over time – all patients ..........................................................................................................................48
5.5 The influence of tumour presence on changes in nutritional status prior to and during chemotherapy .....................................................................................................................50
5.5.1 Patient characteristics prior to starting chemotherapy ...........................................50
5.5.2 The influence of tumour presence on nutritional status .........................................51
5.5.3 The influence of tumour presence on inflammatory status ....................................54
5.5.4 The influence of tumour presence on fatty acid status ..........................................54
5.6 The influence of tumour presence on interrelationships between nutritional, inflammatory and fatty acid status over time .....................................................................56
6.1 Changes in nutritional, inflammatory and fatty acid status during chemotherapy ............61
6.2 Interrelationships between nutritional, inflammatory and fatty acid status over time .......62
6.3 The influence of tumour presence on changes in nutritional, inflammatory and fatty acid status ...........................................................................................................................63
6.4 Strengths and limitations ....................................................................................................66
PG-SGA Patient Generated Subjective Global Assessment
PIF Proteolysis Inducing Factor
PUFA Polyunsaturated Fatty Acid
QOL Quality of Life
RD Registered Dietitian
SEE Standard Error of Estimation
SFA Saturated Fatty Acid
SPM Specialized Pro-resolving Lipid Mediators
TLC Thin-Layer Chromatography
TNF-α Tumour Necrosis Factor Alpha
TSF Triceps Skin Fold
TX Thromboxane
UBW Usual Body Weight
xiii
Glossary
Adjuvant chemotherapy: Chemotherapy given after the primary cancer treatment (i.e. after
surgery), to lower the risk of cancer recurrence (National Cancer Institute)
Anorexia: The loss of appetite or desire to eat.
Biotherapy: The use of living organisms, substances made from living organisms, or laboratory
made substances to treat disease. This includes monoclonal antibodies, protein-targeted
therapies, angiogenesis inhibitors, cytokines, and vaccines (National Cancer Institute, 2013).
Cachexia: In cancer, cachexia is defined as “a multifactorial syndrome characterised by ongoing
loss of skeletal muscle mass (with or without loss of fat mass) that cannot be fully reversed by
conventional nutritional support and leas to progressive functional impairment” (Fearon et al.,
2011).
Functional status: The ability to perform basic activities of daily living such as bathing,
dressing, transferring in and out of a bed or chair, toileting and eating, and instrumental activities
of daily living such as using the telephone, shopping, preparing food, housekeeping/laundry,
using transportation, managing medications, and managing finances (Brown et al., 2017).
Nutrition impact symptoms: Symptoms that impede nutritional intake, digestion, absorption
and utilization (Levin, 2013).
Palliative chemotherapy: Chemotherapy given to provide symptom control, improve quality of
life, and improve survival, in a non-curative setting (Roeland and LeBlanc, 2016).
Perioperative chemotherapy: Chemotherapy around the time of surgery or a combination of
pre- and post-operative chemotherapy.
Pre-operative chemotherapy: Chemotherapy given prior to surgery.
1
Introduction In 2016, it was estimated that 202,400 Canadians would develop cancer. It is the leading cause of
death in Canada with an estimated 216 deaths every day from the disease. Gastrointestinal (GI)
cancer, which may include cancer of the esophagus, stomach, pancreas, liver, colon, and rectum
was estimated to account for approximately 19% of all new cancer cases (Canadian Cancer
Society’s Advisory Committee on Cancer Statistics, 2016).
Patients with GI cancer often present with weight loss prior to starting chemotherapy and are at
risk for further weight loss during anticancer treatment. Reduced dietary intake, weight loss and
loss of lean body mass (LBM) contribute to poor nutritional status and/or cancer-related
cachexia. A compromised nutritional status prior to and during treatment has been associated
with reduced functional status, poor treatment tolerance, poor quality of life (QOL), and
ultimately shorter survival times (Andreyev et al., 1998; Deans et al., 2009; Dewys et al., 1980).
There are numerous factors involved in cancer-related malnutrition and cachexia, including
anorexia, treatment-related side effects, and alterations in intermediary and energy metabolism.
Standard nutrition interventions or medical nutritional therapy (MNT) provided by a registered
dietitian (RD) for patients receiving chemotherapy may involve managing nutrition impact
symptoms through diet education and other specialized diet interventions. Cancer-related
malnutrition and the associated weight loss and loss of LBM continues to be a predominant
problem for many patients with advanced cancer, despite traditional nutrition interventions such
as dietary counselling or the use of nutritional supplements (Tisdale 2002).
The inefficacy of standard nutrition therapy may be related to inflammation, more specifically,
the acute-phase response (APR). The APR is a common feature in patients with advanced cancer
and is associated with a poor prognosis. It is characterized by reprioritization of protein synthesis
for the production of acute-phase proteins such as serum C-reactive protein (CRP) (Barber et al.,
1999a; Stephens et al., 2008). In patients with gastroesophageal cancer, it was found that 83% of
patients present with weight loss at diagnosis and that an elevated serum CRP is an independent
predictor of the degree of weight loss (Deans et al., 2009). Cytokines are the predominant
regulators of the APR and interleukin-6 (IL-6) and tumour necrosis factor alpha (TNF-α) are
known to influence protein loss, anorexia, and to decrease gastric emptying and intestinal
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motility (Stephens et al., 2008). In patients with locally advanced GI cancer and weight loss,
appetite was significantly lower in patients with an APR versus those without. Furthermore,
there was a significant reduction in survival in patients with an APR (O’Gorman et al., 1999).
This underscores the importance of considering the role of inflammation on nutritional decline in
cancer patients.
There is potential that the inflammatory response can be influenced by an individual’s fatty acid
(FA) status, given that eicosanoids are generated from 20-carbon polyunsaturated fatty acids
(PUFA) (Calder, 2006). n-6 FAs such as arachidonic acid (AA), and n-3 FA such as
eicosapentaenoic acid (EPA), give rise to inflammatory lipid mediators such as thromboxanes,
prostaglandins and leukotrienes (Colomer et al., 2007) and also give rise, along with
docosahexanoic acid (DHA) to compounds that help to resolve inflammation (Serhan and
Petasis, 2011). Eicosanoid production begins with the release of PUFAs from membrane
phospholipids. AA tends to produce more potent inflammatory eicosanoids compared to EPA.
Therefore, altering the composition of membrane phospholipids in favour of n-3 FA may help
attenuate the inflammatory response (Mocellin et al., 2016).
Altered FA levels such as elevated levels of AA have been demonstrated in patients with
advanced cancer and n6:n3 ratios have been inversely associated with body mass index (BMI)
(Pratt et al., 2002). FA alterations have also been found to differ by tumour type and the presence
or absence of weight loss, and the presence of inflammation (Zuijdgeest-Van Leeuwen et al.,
2002). Moreover, chemotherapy may be another possible cause of altered FA composition in
plasma phospholipids with one study showing very low levels of long chain PUFAs in three
patients following high dose chemotherapy (Pratt et al., 2002). These alterations in the FA
composition of plasma phospholipids could affect the extent and duration of the APR, and
subsequently nutritional status in cancer patients.
Some studies have demonstrated a potential beneficial effect of n-3 supplementation alone or as
part of an oral nutrition supplement on attenuating weight loss and altering markers of an APR.
These results have been inconsistent and have been primarily in patients with advanced
pancreatic cancer or in heterogenous cancer groups, presenting with weight loss, and generally
not receiving anti-cancer treatment such as chemotherapy. Consequently, there is a lack of
research on the occurrence and etiology of nutritional decline in gastric and colorectal cancer
3
(CRC) patients receiving first-line chemotherapy and inconclusive evidence for the role of n-3
supplements in this population.
Thus, the aim of this dissertation is to enhance knowledge of the potential mediators of the
decline in nutritional status in patients with gastric and CRC undergoing chemotherapy, with a
focus on inflammation and FA levels. This new data may contribute towards the development of
specialized nutrition interventions such as the use of n-3 supplementation in this population.
4
Literature review The purpose of this chapter is to provide an overview of GI cancer, chemotherapy treatment for
gastric cancer and CRC, the potential implications of the disease and treatment on nutritional
status, and the role of MNT in maintaining or improving nutritional status in GI cancer patients
receiving treatment. This chapter will also discuss factors affecting nutritional status in cancer,
the potential role of inflammation in the decline in nutritional status, and finally the potential of
FA in modulating inflammation and nutritional status.
2.1 Gastrointestinal cancer GI cancer, including gastric cancer and CRC accounts for approximately 22% and 17% of new
cancer cases in Canadian males and females, respectively (Canadian Cancer Society’s Advisory
Committee on Cancer Statistics, 2016). While GI cancer may refer to multiple sites within the GI
system, this dissertation focuses solely on gastric cancer and CRC.
Gastric cancer is the fifth most common cancer worldwide and the third most common cause of
death from cancer (World Cancer Research Fund International/American Institute for Cancer
Research, 2016). Risk factors for gastric cancer include smoking, infection with Helicobacter
Pylori, industrial chemical exposure, alcohol, consumption of foods preserved with salting,
consumption of processed meat, being overweight, and obesity (World Cancer Research Fund
International/American Institute for Cancer Research, 2016).
CRC is the third most common cancer worldwide, and the second most common cancer in
Canada (Canadian Cancer Society’s Advisory Committee on Cancer Statistics, 2016; World
Cancer Research Fund / American Institute for Cancer Research, 2011). It is linked to obesity, a
sedentary lifestyle, smoking, and consumption of red and processed meat, and alcohol intake.
Dietary fibre intake, and physical activity likely reduces the risk of developing CRC, and
consumption of milk, garlic, and calcium may also protect against CRC (World Cancer Research
Fund / American Institute for Cancer Research, 2011).
Survival in gastric cancer and CRC is impacted by the stage of disease at time of diagnosis. The
overall five-year survival for gastric cancer ranges from 67% for localized disease, and decreases
5
to 5% for distant or metastasized disease. In CRC, overall five-year survival ranges from >90%
for localized disease, down to 13.5% for metastasized disease (Howlader et al., 2015).
Individuals with GI cancer often present with symptoms that influence nutritional risk and may
adversely affect treatment outcomes. These symptoms include reflux, reduced appetite,
abdominal pain, nausea and vomiting, dysphagia, anemia and weight loss in individuals with
gastric cancer, and bleeding, obstruction and abdominal pain in individuals with CRC (Canadian
Cancer Society’s Steering Committee on Cancer Statistics, 2011).
2.1.1 Treatment in gastrointestinal cancer
Treatment for GI cancer may include chemotherapy, surgery, biotherapy, and radiation or a
combination of modalities. The type of treatment depends on the type and stage of cancer and the
intent of treatment, which may be curative, or palliative, the latter of which focuses on symptom
management in a non-curable setting. This study focuses on patients receiving chemotherapy.
Chemotherapy may be used pre-operatively, peri-operatively, or in a palliative setting. Pre-
operative chemotherapy is given with the intent of decreasing tumour burden prior to surgery.
Chemotherapy may also be used peri-operatively or as adjuvant therapy following surgical
resection. In a palliative setting for metastatic disease, chemotherapy may be used to extend
survival, control symptoms, and improve quality of life (QOL). Chemotherapy regimens
involving the use of 5-fluorouracil are commonly used in gastric cancer and CRC along with
other cytotoxic drugs. These cytotoxic drugs may be used with or without biotherapy, for
example the drugs Bevacizumab (Avastin®) or Trastuzumab (Herceptin®), which are monoclonal
antibodies that bind to specific growth factors and prevent the growth, progression or survival of
cancer cells.
The primary treatment for early stage gastric cancer is surgical resection alone or in combination
with perioperative chemoradiation or post-operative radiation/chemoradiation (Ajani et al., 2016;
Knight et al., 2013). The current standard for treatment of advanced gastric cancer (non-
resectable, locally advanced or metastatic adenocarcinoma), is first-line chemotherapy with
fluorouracil-based combination regimens. Common regimens include ECX, ECF, or FOLFOX
with the addition of Trastuzumab for HER-2 positive patients (Ajani et al., 2016; Mackenzie et
al., 2011). Another regimen under investigation as a first-line treatment in metastatic gastric or
gastroesophageal junction adenocarcinoma is IXO (Table 4-1).
6
Patients with resected CRC who are at a high risk for recurrence will typically undergo adjuvant
chemotherapy with FOLFOX, XELOX or Xeloda (Meyers et al., 2016). For cases in which there
are resectable metastases, for example the liver, patients may undergo surgical resection
followed by adjuvant chemotherapy with FOLFOX, XELOX, or Xeloda, or may undergo
neoadjuvant chemotherapy. In patients with metastatic CRC, the standard first-line treatment is
chemotherapy with FOLFIRI or FOLFOX with or without the use of Bevacizumab (Avastin®)
(Welch et al., 2010).
As previously mentioned, patients with GI cancer often present with symptoms related to the
presence of the tumour that may affect gastric motility, or may contribute to obstructive
symptoms such as nausea, vomiting, diarrhea, constipation or abdominal pain. These symptoms
can subsequently affect nutritional risk and nutritional status. This nutritional risk may be further
exacerbated from common side effects associated with chemotherapy, such as poor appetite,
mouth sores, nausea and vomiting, constipation and diarrhea. Factors affecting nutritional risk, or
nutrition impact symptoms, should be addressed through standard MNT.
2.1.2 Standard medical nutrition therapy in oncology specific to gastrointestinal cancer and chemotherapy
GI cancer patients are at risk for poor nutritional status from both the disease itself and due to
treatment, which may include surgery, radiation, chemotherapy, or a combination of modalities.
Patients often present with weight loss prior to starting chemotherapy and further weight loss
may occur due to side effects associated with antineoplastic therapy. Side effects may include
anorexia, nausea, vomiting, constipation, diarrhea, mucositis or stomatitis, dysgeusia, or taste
alterations, and fatigue. The Academy of Nutrition and Dietetics recommend that RDs, as part of
the interdisciplinary oncology team, provide nutrition care to adult oncology patients receiving
chemotherapy or radiation therapy (Thompson et al., 2017). The Nutrition Care Process is a
standardized method of administering nutrition care and involves nutrition assessment, diagnosis
of nutrition-related problems, evidence-based interventions, and monitoring and evaluation of
those interventions (Elliott, 2006). Within the Nutrition Care Process there are MNT protocols
which outline standardized steps in completing individualized nutrition assessments, the content
and frequency of care, and the measurement of outcomes to manage specific diseases (Elliott,
2006). Nutrition care provided by an RD has been associated with improved treatment outcomes
(Ravasco et al., 2012), QOL (Ravasco, 2005), reduced hospital admissions and length of stay
7
Table 2-1. Chemotherapy protocols, duration, and common side effects
Regimen Drugs Indications Frequency Common Side Effects with Nutritional Implications
Common Supportive Medications
ECF Epirubicin Cisplatin Fluorouracil
Neoadjuvant/Adjuvant Gastric Cancer Every 21 days Nausea, vomiting, stomatitis,
diarrhea, anorexia
Aprepitant* x 3 days; Ondansetron 8 mg BID x 1 day; Dexamethasone 8 md OD x 3 days**
ECX Epirubicin Cisplatin Xeloda
Palliative Advanced Gastric/Gastroesophageal Every 21 days Nausea, vomiting, stomatitis,
diarrhea, anorexia
Aprepitant* x 3 days; Ondansetron 8 mg BID x 1 day; Dexamethasone 8 mg OD x 3 days**
ToGA Cisplatin Xeloda Herceptin
Palliative Gastric Every 21 days Nausea, vomiting, diarrhea, mucositis, anorexia, abdominal pain
Aprepitant* x 3 days; Ondansetron 8 mg BID x 1 day; Dexamethasone 8 mg OD x 3 days**
IXO Irinotecan Xeloda Oxaliplatin
Palliative Metastatic Gastric/Gastroesophageal Every 21 days Nausea, diarrhea Ondansetron 8 mg BID x 3 days;
Dexamethasone 8 mg BID x 3 days
Xeloda Xeloda Palliative Advanced Colorectal Every 21 days Nausea, vomiting, diarrhea, mucositis, abdominal pain None
FOLFOX +/- Avastin
Folinic Acid Fluorouracil Oxaliplatin
Adjuvant/Palliative Advanced Colorectal Every 14 days Nausea, vomiting, diarrhea,
mucositis, abdominal pain Ondansetron 8 mg BID x 3 days; Dexamethasone 8 mg BID x 3 days
FOLFIRI +/- Avastin
Folinic Acid Fluorouracil Irinotecan +/- Avastin
Palliative Advanced/Metastatic Colorectal Every 14 days Nausea, vomiting, anorexia,
diarrhea, mucositis, abdominal pain Ondansetron 8 mg BID x 3 days; Dexamethasone 4 mg BID x 3 days
Cancer Care Ontario Drug Formulary * 125 mg on day 1, 80 mg on days 2 and 3. ** Aprepitant results in decreased clearance of dexamethasone by half, therefore dexamethasone dose equivalent to 16 mg daily.
8
(Odelli et al., 2005; Paccagnella et al., 2010), improved appetite (Ravasco, 2005), improved
survival times (Andreyev et al., 1998; Dewys et al., 1980). There are numerous factors involved
in the etiology of cancer-related malnutrition and cachexia including decreased energy and
nutrient intake from anorexia, treatment-related side effects, and GI dysfunction and dysmotility
(Palesty and Dudrick, 2003). Additionally, effects of the tumour on intermediary and energy
metabolism may lead to the breakdown of fat and muscle.
Nutrition interventions aimed at stabilization of weight and ensuring adequate nutrition intake to
support maintenance of nutritional status have been associated with improved treatment
tolerance and outcomes (Ravasco, 2005; Ravasco et al., 2012), improved QOL (Ravasco, 2005),
and reduced hospital admissions (Paccagnella et al., 2010). Furthermore, stabilization of weight
during chemotherapy has been associated with improved survival (Andreyev et al., 1998).
Cancer-related malnutrition and cachexia however continues to be a predominant problem for
many patients despite standard nutrition interventions (Tisdale, 2002).
Inflammation, specifically the APR, may play a role in the continued and progressive decline in
nutritional status despite nutrition therapy. Inflammatory cytokines are the predominant
regulators of the APR and IL-6 and TNF-α are known to influence protein loss, anorexia,
decreased gastric emptying and intestinal motility (Argilés et al., 2005; Stephens et al., 2008).
FA may modulate the inflammatory response by altering eicosanoid production as suggested in
n-3 supplementation studies. This ability to modulate the inflammatory response and
subsequently nutritional status may be influenced by an individual’s FA levels, which could be
affected by dietary intake, disease burden and treatment. Even in healthy individuals, plasma n-3
FA concentrations have been shown to be inversely related to CRP concentrations with higher
levels of inflammation being associated with lower levels of total n-3 FA, EPA, and
docosapentaenoic acid (Micallef et al., 2009). In cancer patients, additional factors affecting
inflammation and FA levels, altered n-3 and n-6 FA levels could predispose a patient to
32
inflammation or limit the resolution of inflammation leading to poor nutritional status during
chemotherapy.
There is limited research describing the nutritional and inflammatory status in patients with
gastric cancer and CRC and most studies have focused on patients not receiving chemotherapy.
Additionally, many studies involving n-3 supplementation have been in patients with advanced
disease already presenting with progressive weight loss. Recalling that the success of MNT may
depend on the early identification and intervention for patients at high risk for nutritional decline,
there is an interest in examining the potential for modulation of inflammation earlier in the
disease trajectory. For example, there may be a potential benefit from n-3 supplementation prior
to or during anti-cancer treatment rather than in a palliative setting in which patients are more
likely to be in a state of refractory cachexia.
Knowledge of potential mediators of the decline in nutritional status that may occur in patients
with gastric cancer and CRC undergoing treatment is necessary for designing proactive
interventions that can prevent weight loss and associated complications. There may be a potential
benefit of n-3 supplementation in this population however there is uncertainty as to which
patients may be the most vulnerable (i.e. low levels of n-3 FA or high levels of inflammation) or
the most likely to benefit, and if there is an optimal time for potential supplementation (i.e. at the
beginning of chemotherapy). No other study to our knowledge has prospectively studied factors
predisposing patients with gastric cancer and CRC to nutritional decline during first-line
chemotherapy, with a focus on the interrelationships between nutritional status, inflammation
and FA levels. Furthermore, no study to our knowledge has compared patients with resected
disease to patients with non-resected disease to identify effects of tumour burden in patients
receiving chemotherapy.
The purpose of this study was to describe changes in nutritional, inflammatory and FA status
prior to and during chemotherapy, to describe changes in nutritional status in relation to levels of
inflammation and FA in patients with gastric cancer and CRC, and to identify factors associated
with nutritional depletion during treatment.
We hypothesized that in patients with gastric cancer and CRC, a decline in nutritional status
during the course of chemotherapy would be associated with increasing levels of inflammation
and decreasing levels of n-3 FA.
33
3.2 Objectives 1) To describe changes in nutritional status as measured by weight, PG-SGA score and
global rating, skinfold thickness, BIA, and dietary intake, as well as changes in
inflammation and n-3 FA status in patients with gastric cancer and CRC prior to and
during chemotherapy;
2) To investigate the interrelationships between changes in nutritional status, inflammation,
and FA levels in patients with gastric cancer and CRC receiving chemotherapy;
3) To compare nutritional outcomes in patients undergoing adjuvant chemotherapy (i.e.
following surgical resection of the tumour) with those undergoing palliative
chemotherapy (non-resectable/metastatic disease), as a control to account for the
influence of tumour burden.
34
Methods
4.1 Study design and participants This was a prospective, observational study of patients with newly diagnosed gastric cancer or
CRC attending the Medical Day Care Unit at St. Michael’s Hospital (Toronto, Canada) for first-
line adjuvant, neoadjuvant or palliative treatment with 5-fluorouracil-based chemotherapy.
Participants were recruited by consecutive sampling between January 2011 and June 2013.
Patients with physical/functional obstruction to the GI tract, undergoing concurrent treatment
with radiation, or those with a life expectancy < 3 months were excluded. Study participants
were assessed at 4 time points coinciding with scheduled clinic visits for chemotherapy.
Measurements were completed prior to the infusion of cycle 1 of chemotherapy (baseline), and
prior to administration of cycles 2, 3 and 4 of chemotherapy (Figure 4-1). During the study,
patients received standard medical nutrition therapy by the study RD which included dietary
interventions (education, diet modifications, use of oral nutrition supplement products) to
support maintenance of nutritional status during treatment. The study protocol was approved by
the St. Michael’s Hospital Research Ethics Board. Written informed consent was obtained from
each study participant (Appendix 8.2).
4.2 Measurements
4.2.1 Chemotherapy
All patients were receiving standard first-line 5-fluorouracil based chemotherapy for gastric
cancer or CRC as per provincial, national and international guidelines. ECF, ECX, ToGA, IXO
and Xeloda were administered every 3 weeks. FOLFOX +/- Avastin and FOLFIRI +/- Avastin
were administered every 2 weeks. Patients received supportive medications in standard dosages
(aprepitant, ondansetron and dexamethasone) in conjunction with chemotherapy (Table 2-1).
4.2.2 Blood collection and processing
Fasting blood samples were collected during the morning of regular clinic, prior to starting
chemotherapy (baseline) and prior to infusion of cycles 2, 3 and 4. Blood draws coincided with
routine pre-chemotherapy blood work to minimize participant burden. Samples were collected in
vacuum tubes containing EDTA for determination of plasma phospholipid FA profiles and
35
Figure 4-1. Study schedule
*Study duration dependent on chemotherapy regimen. See Table 4-1. **Blood work and measurements taken on day 1 of each cycle prior to infusion of chemotherapy. Dietary intake recorded prior to baseline and prior to each subsequent cycle of chemotherapy
assessment tool validated in the oncology population. Nutritional risk was based on the PG-SGA
score with higher scores indicating higher nutritional risk and a greater need for nutrition
intervention. Nutritional status was assessed using the PG-SGA global rating (A=well-nourished,
B=moderate/suspected malnutrition, C=severely malnourished). The PG-SGA is described in
more detail in section 2.2.1. Height and weight were used to determine BMI (kg/m2). Body
composition was estimated using the sum of four skinfolds measured. Percent body fat was
obtained from an age- and sex-specific table with values based on the logarithmic transformation
of the sum of the four skinfolds using linear regression equations by Durnin and Womersley
(Durnin and Womersley, 1973). Fat mass was then determined by multiplying percent body fat
and current body weight. FFM was estimated by subtracting fat mass from current body weight.
Additionally, body composition was estimated with BIA using a single-frequency (50kHz)
tetrapolar technique (Quantum II Analyzer, RJL Systems, Detroit, USA). Measurements of
resistance and reactance were performed with patients in a supine position on the right side of the
body. Two electrodes were placed on the dorsum of the right hand and two were placed on the
37
dorsum of the right foot (Lukaski 1985). Measurements were repeated three times and the mean
of the measurements was used for analysis. Patients with ascites, peripheral edema, or receiving
IV fluids were excluded from BIA analysis. FFM from BIA was calculated using Kotler’s
equation (Kotler 1996). Percent body fat from BIA was estimated by using subtracting the FFM
value from current body weight to obtain a value for fat mass. Fat mass was then divided by the
current body weight and multiplied by 100 to obtain percent body fat. The trajectory of
nutritional status over time was additionally characterized using AMA. AMA was calculated
from MAC and TSF using the equations by Heymsfield et al (Heymsfield et al., 1982). Handgrip
strength was measured using a hydraulic hand dynamometer (Jamar, Lafayette Instrument,
Lafayette, Indiana, USA) according to the recommended standard procedures. Three maximal
values were recorded to the nearest 0.5 kg, and the mean of the 3 measurements was used for
analysis.
4.2.5 Dietary intake
Three-day food records were completed before baseline and prior to each subsequent study visit.
Patients were provided with oral and written instructions prior to the start of the study and were
provided with measuring utensils (measuring spoons and cups) to assist with accurate
quantification of food and beverages consumed. Food records were reviewed with patients at
each study visit for completeness. 24-hour diet recalls were completed for patients who did not
or were not able to complete a 3-day food record. Nutrient analysis was completed using The
Food Processor® SQL (ESHA Research, Version 10.12, Salem, Oregon, USA) with values from
the Canadian Nutrient File 2007b database. Patients were also asked to report use of any vitamin,
mineral, or natural health products. During the study, patients received MNT by an RD for any
nutrition impact symptoms identified on the PG-SGA tool, and food records were used to
optimize dietary intake to support maintenance of nutritional status.
4.2.6 Inflammatory markers
Plasma concentrations of high-sensitivity CRP were measured using an immunoturbidimetric
assay on a Beckman-Coulter LX-20 analyzer with a coefficient of variation of < 8%. Serum
concentrations above of CRP greater than 10 mg/L were considered to indicate the presence of
inflammation and an APR. Serum albumin concentrations were determined using the bromcresol
purple dye-binding technique on the SYNCHRON LX system. Plasma concentrations of the
38
cytokines IL-6 and TNF-a were measured in duplicate using enzyme-linked immunosorbent
assay (ELISA; Quantikine, R&D Systems, Minneapolis, USA). The detection limits of kits were
0.7 pg/mL and 5.5 pg/mL for IL-6 and TNF-a, respectively and coefficient of variation was <
8% for both assays. Analyses for CRP and serum albumin were performed in the core laboratory,
Department of Laboratory Medicine, St. Michael’s Hospital. Cytokine analysis was performed in
the laboratory of Dr. Philip Connelly, Keenan Research Centre for Biomedical Science, St.
Michael’s Hospital.
4.2.7 Plasma fatty acids profile
The FA profile of plasma phospholipids was quantified in the laboratory of Dr. Richard Bazinet
at the University of Toronto (Toronto, Canada). To assess FA, plasma total lipids were extracted
from plasma using chloroform/methanol (2:1, v/v) according to the Folch method (Folch et al.,
1957). Thin-layer chromatography (TLC) was used to separate the lipid classes. TLC plates were
activated by heating at 100°C for 1 hour. Total lipids were then loaded onto the plates and placed
in a tank with solvents. FA fractions were separated along with authentic standards in heptane–
diethyl ether–glacial acetic acid (60:40:2, v/v). Bands corresponding to the plasma lipid fractions
were visualized under UV light, after staining with 8-anilino-1-naphthalene sulphonic acid
(0·1 %, w/v). Heptadecanoic acid (C17:0) (Sigma, St. Louis, Missouri, USA) was added as an
internal standard to an aliquot of the plasma and the phospholipid band scraped. Total lipids were
extracted and FA were converted to fatty acid methyl esters (FAME) using 14% boron
triflouride-methanol at 100˚C for 1 hour (Sigma). FAME were analyzed by gas-liquid
chromatography using a capillary column (VF-23ms, 30 m × 0·25 mm inner diameter × 0·25 µm
film thickness; Agilent Technologies) and flame ionization detector, in a Varian-430 gas
chromatograph (Varian, Inc.). Samples were injected in splitless mode with the temperature of
the injector and detector ports set at 250°C. FAME were eluted using a temperature program set
initially at 50˚C for 2 min, increased at 20˚C/min and held at 170˚C for 1 minute and then
increased at 3˚C/min and held at 212˚C for 5 minutes. The carrier gas used was helium, set at a
constant flow rate of 0.7 ml/min. Peaks were identified by the retention times of FAME
standards (Nu-Chek-Prep, Elysian, Minnesota, USA) and FA concentrations (nmol/mL) were
calculated by proportional comparison of GC peak areas with that of the C17:0 internal standard
(Nishi et al., 2014). The inter and intra-assay coefficients of variation were < 4%. Total n-3
PUFAs represent the sum of alpha-linolenic acid, eicosatrienoic acid, eicosapentaenoic acid,
39
docosapentaenoic acid and docosahexaenoic acid. Total n-6 PUFAs represent the sum of linoleic
acid, gamma-linolenic acid, eicosadienoic acid, arachidonic acid, adrenic acid and
docosapentaenoic acid. Fatty acids were expressed as amounts (nmol/mL) and as a proportion
(%) of total PL.
4.2.8 Other data
Age, sex, diagnosis, stage of disease based on the American Joint Committee on Cancer TNM
staging system, location of metastases, prior surgery, chemotherapy regimen, and chemotherapy
dose reductions were recorded from patient medical records.
4.3 Statistical analysis Baseline descriptive analysis was performed using SPSS version 19.0. Results are reported as
median with range unless otherwise specified. Differences in baseline variables were assessed
using Fisher’s Exact Test for categorical variables, and the Mann-Whitney U Test for continuous
variables. The remaining analysis was completed using the open source software R, version
3.3.3. To determine changes in nutritional, inflammatory, and fatty acid status over time, a linear
mixed effect (LME) model with a random intercept was used. Model residuals were assessed for
normality and homogeneity of variance. Analyses were done with and without patients with self-
reported use of fish oil supplements (n=7) and patients with supplemental intakes of flaxseed oil
(n=1). To determine the association between covariates and outcomes of nutritional status, and to
determine if changes over time persisted after adjusting for known confounding factors, LME
model was used for each nutritional status outcome (weight, FFM from BIA and skinfold
anthropometry). The best LME for each nutritional status outcome was first chosen by running a
backwards selection algorithm. Variables that did not meet the criteria of having a Wald p-value
<0.05 were removed from the model until only significant variables remained. Visit was added to
each final model as a covariate to determine if the association over time remained significant
after adjusting for other known confounding factors. Variance inflation factors were calculated
for the final models to determine if multicollinearity was an issue. To determine if the
relationship between inflammation, fatty acid status and nutritional status differs depending on
tumour burden (resected versus non-resected tumour), the best LME model was used to adjust
for the interaction between tumour presence and visit. All p-values are two-sided and unadjusted.
Significance was considered at p<0.05.
40
Results
5.1 Patient population One-hundred and three patients were screened of which 34 did not meet inclusion criteria; 10
patients declined participation due to language barrier, feeling overwhelmed, or feeling that
participation would be too burdensome; and 15 patients were excluded due to the decision to
have treatment at another facility, alcoholism or inability to obtain consent prior to starting
chemotherapy. Of the 44 patients who agreed to participate, one expired prior to starting the
study, one started treatment at another facility and one did not start chemotherapy due to failure
to cope/poor performance status. Figure 5-1. provides details of patient accrual and study
completion according to whether patients had resected disease (undergoing adjuvant
chemotherapy post-surgery), or non-resected disease (undergoing neoadjuvant/palliative
chemotherapy).
5.2 Patient characteristics prior to starting chemotherapy Forty-one patients started the study. Baseline patient characteristics are shown in Table 5-2.
Twenty-three patients were males and 18 were females, with a mean age of 58.5 ± 11.3 years.
CRC was the most common diagnosis (68%). More than half the patients presented with Stage
IV disease. Most patients (58.5%) received FOLFOX with or without Avastin, or IXO; 22%
received FOLFIRI with or without Avastin; 14.6% received ECF, ECX or ToGA (Cisplatin,
Herceptin and Xeloda); and 4.9% received Xeloda alone (data not shown). Supportive
medications in standard dosages (aprepitant, ondansetron and dexamethasone) were provided in
conjunction with chemotherapy. The median duration of participation was 42 days, with a
minimum participation of 1 day (baseline visit only) and a maximum participation of 77 days
(additional time due to toxicity-related chemotherapy delays). Seven patients reported use of fish
oil supplements prior to starting chemotherapy.
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Figure 5-1. Flowchart of study participants
*Other reasons: Alcoholism (n=1); Unable to obtain consent prior to treatment (n=10); No show (n=1); Planned treatment at another facility (n=3).
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Table 5-1. Baseline patient characteristics based on tumour presence1 All patients (n=41)2 Resected (n=16)3 Non-resected (n=25)4 p
Means ± SD, frequencies, and median (range). Fisher’s Exact Test and Mann-Whitney U test used for categorical and continuous variables, respectively. Abbreviations: BMI, body mass index; PG-SGA, patient-generated subjective global assessment; BIA, bioelectrical impedance analysis; FSA, four-site skinfold anthropometry; AMA, arm muscle area; CRP, C-reactive protein; IL-6, interleukin-6; TNF-α, tumour necrosis factor α; PL, phospholipid; ALA, alpha-linolenic acid; LA, linoleic acid; AA, arachidonic acid; EPA, eicosapentaenoic acid; DHA, docosahexaenoic acid.
1 Resected = tumour resected (adjuvant therapy), Non-resected = tumour in situ (palliative or neoadjuvant/perioperative therapy) 2 Serum albumin, IL-6, Plasma PL fatty acids: n=39; PG-SGA, AMA, Handgrip strength, CRP, TNF-a: n=38; BIA: n=34; FSA: n=36; Dietary intake: n=37 3 PG-SGA, AMA, Dietary intake, Handgrip strength, Serum albumin, IL-6, CRP, TNF-a, Plasma PL fatty acids: n=15; FSA: n=14; BIA: n=13 4 Serum albumin, IL-6, Plasma PL fatty acids: n=24; PG-SGA, AMA, Handgrip strength, CRP, TNF-a: n=23; FSA, Dietary intake: n=22; BIA: n=22 5 Fish oil supplement use defined as patient-reported use of either ‘fish oil’ or ‘calamari oil’. 6 PG-SGA self-reported functional status based on ECOG (Eastern Cooperative Oncology Group) performance scale 7 Total n-3 PUFAs represent the sum of alpha-linolenic acid, eicosatrienoic acid, eicosapentaenoic acid, docosapentaenoic acid and docosahexaenoic acid. 8 Total n-6 PUFAs represent the sum of linoleic acid, gamma-linolenic acid, eicosadienoic acid, arachidonic acid, adrenic acid and docosapentaenoic acid.
44
5.3 Changes in nutritional, inflammatory and fatty acid status during chemotherapy – all patients
5.3.1 Nutritional status
Prior to starting chemotherapy, 53% of patients presented with moderate or severe malnutrition
based on the PG-SGA and were classified in the B or C category. The median PG-SGA score
was 7 (range 1-20) suggesting nutritional risk requiring intervention by a dietitian. The most
frequent nutrition impact factors included early satiety (34%), no appetite (26%), and fatigue
(13%). Median energy and protein intake was 1771.1 kcal/d and 78.1 g/d, respectively. Median
carbohydrate, protein and fat intakes were within the acceptable macronutrient distribution
ranges for healthy populations. Over the course of the study, there was significant change in the
ratio of well-nourished to malnourished individuals with 53% of individuals at baseline
presenting with malnutrition based on the PG-SGA versus 21% by visit 4 (p<0.01, Table 5-2).
There was also a significant increase in energy intake over time with an average increase of 85
kilocalories per visit (p < 0.01).
5.3.2 Inflammatory status
CRP concentrations ranged widely from 0.5 to 144.2 mg/L prior to starting chemotherapy
suggesting a wide variability in the presence of an APR. Similarly, concentrations of the
cytokines, IL-6 and TNF-α, and serum albumin also varied widely at baseline. There were no
significant changes in markers of inflammation over time in all patients. Though CRP appeared
to be decreasing over time, this was not statistically significant (Table 5-3).
5.3.3 Fatty acid status
When considering the group as a whole, there was a significant increase in median
concentrations of LA, AA, EPA, DHA, total n-3, total n-6 and total plasma phospholipid FA
over the 4 study visits and a significant decrease in the n6 to n3 ratio over time (Table 5-4).
45
Table 5-2. Markers of nutritional status over time – All patients Baseline (Cycle 1)
n = 411 Cycle 2
n = 402 Cycle 3
n = 373 Cycle 4
n = 354 β p Weight (kg) 71.6 (48.1-105.3) 69.2 (46.0-105.0) 69.0 (47.9-104.0) 68.3 (49.4-103.5) -0.168 0.23
1 Total n-3 PUFAs represent the sum of alpha-linolenic acid, eicosatrienoic acid, eicosapentaenoic acid, docosapentaenoic acid and docosahexaenoic acid. 2 Total n-6 PUFAs represent the sum of linoleic acid, gamma-linolenic acid, eicosadienoic acid, arachidonic acid, adrenic acid and docosapentaenoic acid.
48
5.4 Interrelationships between nutritional, inflammatory and fatty acid status over time – all patients
To examine the influence of inflammation and FA status on changes in nutritional status, a
multivariate analysis focusing on weight, FFM as measured by BIA, and FFM as measured by
FSA as outcomes of nutritional status was completed. These variables were chosen as weight and
FFM are commonly reported in the literature as markers of nutritional status. We also chose to
investigate nutritional risk as an outcome, as measured by the PG-SGA score, given that we were
interested in examining factors affecting nutritional risk. The variables included in each model
were age, sex, tumour stage, diagnosis, calorie intake and protein intake. CRP, IL-6, and TNF-α
were included in the models as markers of inflammatory status. Finally, plasma phospholipid
concentrations of EPA, DHA, AA, total n-3, and total n-6 were selected to examine the influence
of FA status based on the literature demonstrating a potential role for these FA in influencing
nutritional status by modulating inflammation.
5.4.1 Weight
Following backwards selection, the best model for weight included sex, plasma phospholipid
concentrations of DHA and total n-3 (Table 5-5). Females on average weighed 11.8 kg less than
males after adjusting for visit, DHA, and total n-3 FA. There was a positive association between
weight and total n-3 with a 0.02 kg increase for every nmol/mL change in total n-3 (p<0.01), and
a negative association between weight and DHA (β = -0.05, p < 0.01). After adjusting for these
variables (holding sex, DHA and n-3 FA constant), there was a significant decrease in weight
over time by an average of 0.36 kg per visit (p=0.019), when considering all patients together.
Table 5-5. Multivariate model for weight – all patients Variable β SE p
(Intercept) 75.64 2.67 Time (visit) -0.36 0.15 0.02 Sex1 -11.76 3.86 p < 0.01 Plasma DHA -0.05 0.02 p < 0.01 Plasma Total n-3 0.02 0.01 p < 0.001 Linear mixed effects model using a backward selection algorithm including age, sex, tumour stage, diagnosis, total calories/day, total protein/day, CRP, IL-6, TNF-α, and plasma concentrations of EPA, DHA, AA, total n-3 and total n-6.
1 Male = reference
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5.4.2 Fat free mass as measured by BIA and FSA
The best model for FFM as measured by FSA included sex and IL-6 (Table 5-6). The model for
FFM as measured by BIA included sex, IL-6, TNF-α, plasma AA, and plasma total n-6 (Table 5-
7). With respect the inflammatory markers, there was a significant positive association between
FFM and IL-6 as measured by both BIA (β = 0.032, p < 0.01) and FSA (β = 0.04, p < 0.01), and a
significant positive association between FFM as measured by BIA and TNF-α (β = 0.076, p =
0.04). In terms of the influence of FA, there was a significant negative association between
plasma AA and FFM (BIA) with a 0.010 kg decrease in FFM for every nmol/mL increase in AA
(p < 0.01). Conversely, there was a positive association between plasma total n-6 and FFM (BIA,
β = 0.003, p = 0.02). Holding sex and IL-6 constant, there was no significant change in FFM as
measured by FSA over time (β = -0.01, p = 0.94). Similarly, for FFM as measured by BIA, after
controlling for sex, IL-6, TNF-α, and plasma phospholipid concentrations of AA and total n-6,
there was not enough evidence to suggest a change in FFM over time (β = 0.036, p = 0.68).
Table 5-6. Multivariate model for FSA fat free mass – all patients Variable β SE p
(Intercept) 55.38 1.36 Time (visit) -0.01 0.09 0.94 Sex -14.85 2.04 p < 0.001 Il-6 0.04 0.01 p < 0.01 Linear mixed effects model as described in Table 5-5.
1 Male = reference
Table 5-7. Multivariate model for BIA fat free mass – all patients Variable β SE p
(Intercept) 59.45 1.53 Time (visit) 0.04 0.09 0.68 Sex1 -16.58 2.15 p < 0.001 Il-6 0.03 0.01 p < 0.01 TNF-α 0.08 0.04 0.04 Plasma AA -0.01 0.004 p < 0.01 Plasma Total n-6 0.003 0.001 0.02 Linear mixed effects model as described in Table 5-5.
1 Male = reference
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5.4.3 Nutritional risk
The best model for nutritional risk as measured by the PG-SGA score included diagnosis, total
protein intake, IL-6 and plasma phospholipid concentrations of total n-3 FA (Table 5-8). CRC
patients on average had lower nutritional risk scores versus patients with gastric cancer (β =-
4.562, p<0.01). There was also a significant negative relationship between nutritional risk and
protein intake though this was not likely clinically significant with a 0.04 point decrease in
nutritional risk for every gram increase in protein intake (p = 0.02). With respect to inflammatory
markers, there was a significant positive relationship between nutritional risk and IL-6 (β = 0.08,
p = 0.03) concentrations. Lastly, there was a significant negative relationship between nutritional
risk and plasma phospholipid FA concentrations of total n-3 (β = -0.01, p = 0.04). After adjusting
for these variables however, there was no significant change in nutritional risk over time (β =
0.22, p = 0.59).
Table 5-8. Multivariate model for PG-SGA score – all patients Variable β SE p
(Intercept) 16.40 2.36 Time (visit) -0.16 0.29 0.58 Diagnosis1 -4.65 1.54 p < 0.01 Protein intake (g/day) -0.04 0.02 0.02 Il-6 0.08 0.04 0.03 Plasma Total n-3 -0.01 0,01 0.04 Linear mixed effects model as described in Table 5-5.
1 Gastric cancer = reference
5.5 The influence of tumour presence on changes in nutritional status prior to and during chemotherapy
5.5.1 Patient characteristics prior to starting chemotherapy
There was a significant difference in the proportion of patients with gastric cancer versus CRC in
the resected versus non-resected groups (p < 0.01, Table 5.1). Additionally, the non-resected
group had a significantly higher proportion of patients with advanced disease (p < 0.01). While
patients in the resected group had mostly Stage II or Stage III disease, 92% of patients within the
non-resected group had stage IV disease. In the non-resected group, 18 patients with Stage IV
51
disease were receiving palliative chemotherapy, and 7 patients were receiving peri-operative
chemotherapy. With respect to metastatic disease, 60% of patients with non-resected disease had
one site of metastasis and 32% of patients had 2 sites of metastases (data not shown).
5.5.2 The influence of tumour presence on nutritional status
Prior to starting chemotherapy, there was a significantly higher number of malnourished patients
in the non-resected group (14 versus 4, p=0.013, in the non-resected versus resected groups,
respectively). Patients in the non-resected group were also at higher nutritional risk based on the
PG-SGA score, with a higher score indicating a greater need for nutritional intervention (9.5
versus 5, p=0.019), non-resected versus resected, respectively. The difference in nutritional risk
was only apparent with the exclusion of patients reporting fish oil supplement use (data not
shown). Median weight loss prior to starting treatment did not differ significantly between the
two groups (3.3 versus 5.1%, p = 0.082, resected versus non-resected, respectively). There was
no significant difference in median energy or protein intake between the two groups (Table 5-1).
There was no significant difference in FFM as measured by BIA or FSA, however there were
significant differences in percent body fat. Percent body fat from BIA was significantly lower at
baseline in the non-resected group versus the resected group (median 22.3 versus 28.3, p=0.038,
respectively). Percent body fat derived from FSA was significantly lower at baseline in the non-
resected group versus the resected group (median 27.2 versus 35.0, p=0.014, Table 5-1).
Over the course of chemotherapy, there was a significant interaction between tumour presence
and time for weight, BMI, FFM (FSA) and AMA (p < 0.05), and tumour presence and changes
in FFM (BIA, p < 0.01), indicating that the change in these variables over time were dependent
on whether patients had resected or non-resected disease. In patients with resected disease,
weight and BMI were stable during chemotherapy, while these nutritional parameters
significantly decreased in patients with non-resected disease (weight: β = -0.511, p < 0.01; BMI:
β = -0.186, p < 0.01; Tables 5-9 and 5-9.1). In terms of body composition, patients with resected
disease had a significant increase in muscle mass (BIA: β = 0.306, p < 0.01; FSA: 0.26, p = 0.02;
AMA: β = 1.131, p = 0.02) over the course of chemotherapy, while patients with non-resected
disease experienced a decrease in muscle mass (AMA: β = -0.773, p < 0.01). Average calories
consumed per day significantly increased over time in both groups (resected: β = 78.95, p = 0.02;
52
Table 5-9. Markers of nutritional and functional status over time – Resected Baseline (Cycle 1)
1 Total n-3 PUFAs represent the sum of alpha-linolenic acid, eicosatrienoic acid, eicosapentaenoic acid, docosapentaenoic acid and docosahexaenoic acid. 2 Total n-6 PUFAs represent the sum of linoleic acid, gamma-linolenic acid, eicosadienoic acid, arachidonic acid, adrenic acid and docosapentaenoic acid.
Table 5-11.1. Markers of plasma phospholipid fatty acid status over time – Non-resected Plasma phospholipid fatty
1 Total n-3 PUFAs represent the sum of alpha-linolenic acid, eicosatrienoic acid, eicosapentaenoic acid, docosapentaenoic acid and docosahexaenoic acid. 2 Total n-6 PUFAs represent the sum of linoleic acid, gamma-linolenic acid, eicosadienoic acid, arachidonic acid, adrenic acid and docosapentaenoic acid.
58
Similarly, there was a significant interaction between time and tumour presence with FFM as
measured by FSA (Table 5.13), adjusting for sex and IL-6, with FFM decreasing over time in
those with non-resected disease (Figure 5-2b). Consistent with FFM measured by FSA, there was
a significant interaction between time and tumour presence for FFM measured by BIA after
adjusting for sex, IL-6, TNFα, plasma concentrations of AA, and total n-6 (Table 5.14). Again,
predicted FFM increases in the resected group and decreases in the non-resected group (Figure 5-
2c).
There was no evidence to suggest that change in nutritional risk over time as measured by the
PG-SGA score differed depending on whether the patient had their tumour resected or not (Table
5.15, Figure 5-2d).
A sensitivity analysis was also conducted with the removal of patients reporting fish oil or flax
oil use. The results of the multivariate analysis with adjustment for the interaction between
tumour presence and time remained unchanged for weight. The interaction between tumour
presence and time for FFM (BIA) became borderline significant, and the interaction between
tumour presence time for FFM (FSA) was no longer significant (Appendix 8.4).
Table 5-12. Multivariate model for weight with tumour interaction Variable β SE p
(Intercept) 77.78 3.85 Time (visit) 0.24 0.21 0.25 Tumour presence1 -2.45 4.02 0.55 Sex2 -12.63 3.91 p < 0.01 Plasma DHA -0.04 0.02 p < 0.01 Plasma Total n-3 0.02 0.01 p < 0.01 Time*Tumour presence -0.94 0.24 p < 0.001 Linear mixed effects model using a backward selection algorithm including age, sex, tumour stage, diagnosis, total calories/day, total protein/day, CRP, IL-6, TNF-α, and plasma concentrations of EPA, DHA, AA, total n-3 and total n-6, with an adjustment for the interaction between tumour presence and time (visit).
1 Resected = reference 2 Male = reference
59
Table 5-13. Multivariate model for FSA fat free mass with tumour interaction
Variable β SE p (Intercept) 55.43 2.04 Time (visit) 0.26 0.14 0.07 Tumour presence1 0.15 2.19 0.95 Sex2 -14.98 2.10 p < 0.001 Il-6 0.03 0.01 0.02 Time*Tumour presence -0.46 0.18 0.015 Linear mixed effects model as described in Table 5-12.
1 Resected = reference 2 Male = reference
Table 5-14. Multivariate model for BIA fat free mass with tumour interaction
Variable β SE p (Intercept) 60.31 2.20 Time (visit) 0.23 0.13 0.07 Tumour presence1 -0.93 2.28 0.69 Sex2 -16.93 2.22 p < 0.001 Il-6 0.03 0.01 0.02 TNF-α 0.06 0.04 0.07 Plasma AA -0.01 0.004 p < 0.01 Plasma Total n-6 0.003 0.001 0.01 Time*Tumour presence -0.34 0.16 0.04 Linear mixed effects model as described in Table 5-12.
1 Resected = reference 2 Male = reference
Table 5-15. Multivariate model for PG-SGA score with tumour interaction
Variable β SE p (Intercept) 18.29 2.97 Time (visit) 0.22 0.41 0.59 Tumour presence1 -0.75 2.06 0.72 Diagnosis2 -5.57 1.70 p < 0.01 Protein intake (g/day) -0.04 0.02 0.01 Il-6 0.08 0.04 0.04 Plasma Total n-3 -0.01 0,01 0.01 Time*Tumour presence -0.62 0.53 0,24 Linear mixed effects model as described in Table 5-12.
1 Resected = reference 2 Gastric cancer = reference
60
Figure 5-2. Predicted markers of nutritional status by tumour presence
Predicted markers of nutritional status by tumour presence for an average patient using the linear
mixed effects multivariate models (Tables 5.12 to 5.15). Predicted weight (a) for a male patient
with DHA = 85 nmol/mL and total n-3 = 250 nmol/mL; predicted FFM as measured by FSA (b)
for a male patient with an IL-6 = 9 pg/mL; predicted FFM as measured by BIA (c) for a male
patient with an IL-6 = 9 pg/mL, TNF-α = 3.6 pg/mL, AA = 264 nmol/mL, and total n-6 = 887
nmol/mL; and nutritional risk as measured by PG-SGA score (d) for a male patient with
colorectal cancer, IL-6 = 9 pg/mL, AA = 264 nmol/mL, and protein intake of 83 grams/day.
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Appendices
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Appendix 8.1 Summary of fish oil supplementation studies
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Table A8-1. Summary of studies of fish oil supplementation in patients not receiving anti-cancer therapy Study Design Population Intervention Outcomes Results
Wigmore et al. 1996
Open-label, single arm. Results compared with similar population in a previous study.
Patients with unresectable pancreatic cancer (n=18).
2 g/day fish oil capsules, increased weekly to a maximum dose of 16 g/day. Median maximum dose of 12 g fish oil/day = 2 g EPA/day.
Median weight gain of 0.3 kg/month compared to 2.9 kg/month weight loss prior to supplementation. No significant change in TBW, MAMC and TSF. Lower CRP 1 month after supplementation but increased again by 3 months. Significant increase in EPA, DHA and decrease in AA.
Barber et al. 1999b
Non-randomized control trial.
Weight-losing patients with advanced pancreatic cancer. 18 in control (C) and 18 in intervention (I) group. 6 healthy individuals for comparison.
2 cans of fish-oil enriched nutrition supplement/day (Total = 2.18 g EPA, 0.92 g DHA). Mean intake not reported.
Significantly higher concentrations of positive APP and lower negative APP in cancer patients vs. healthy controls. I: No change in APP except increase in transferrin. Median 1 kg weight gain. C: Increase in CRP and decrease in negative APP. Median 2.8 g weight loss.
Barber et al. 2001
Open-label, single arm.
Patients with unresectable pancreatic cancer with ongoing weight loss.
2 cans fish oil-enriched nutrition supplement/day (2.2 g EPA, 0.96 g DHA). Median intake of 1.9 cans/day.
IL-6, soluble TNF receptors, soluble IL-6 receptor, production of IL-β, IL-6, TNF. Hormones (Insulin, cortisol, leptin), PIF, weight.
Median weight gain of 1.0 kg x 3 weeks. Decreased IL-6 production, increased fasting insulin, decreased cortisol-insulin ratio. Decreased proportion of patients with detectable PIF.
Wigmore et al. 2000
Open-label single arm.
Patients with unresectable pancreatic cancer (n-26).
1 g/day for first week, 2 g/day for second week, 4 g/day for third week, 6 g/day thereafter via EPA capsules.
Weight, MAMC, TSF, APR, TBW, energy intake, plasma PL EPA, AA, WHO performance status, survival.
Decreased rate of weight loss, increased percentage of EPA in plasma PL, decreased AA. No change in APR.
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Table A8-1. Summary of studies of fish oil supplementation in patients not receiving anti-cancer therapy Study Design Population Intervention Outcomes Results
Pratt et al. 2002
Randomized, controlled, blinded.
Patients with advanced cancer: 13 in intervention (I), 10 in control (C) group. Burn injury (n=10). High-dose chemotherapy with stem cell transplant (n-3). Healthy subjects (n=6).
I: 18 fish oil capsules per day (180 g EPA, 120 mg DHA per capsule). C: Olive oil.
Fatty acid composition of neutrophils and plasma PL, nutritional status (BMI, total caloric intake, fat intake).
Decreased levels of plasma PL in advanced cancer patients lower than healthy subjects. Decreased PUFA following induction and high dose chemotherapy. After supplementation: I: Increased EPA and DHA in plasma PL. Change in body weight directly correlated with increased EPA content in plasma PL. C: No change in plasma PL composition.
Fearon et al. 2003
Randomized, controlled, double blinded
Patients with unresectable pancreatic cancer with >5% weight loss x 6 months. 95 in intervention (I) and 105 in control (C) group.
2 cans per day of oral supplement. I: n-3 FA and antioxidant enriched nutrition supplement (1.1 g EPA) C: Isocaloric isonitrogenous nutrition supplement. Mean intake of 1.4 cans/day.
I: Increase in total dietary intake (meals plus supplement). 26% reported some intake of supplement but minimal to no increase in plasma EPA. Significant positive correlation between daily supplement intake and weight and LBM, and between plasma EPA and weight and LBM. C: Increase in protein intake. 18% had high EPA levels at week 4 and/or 8. Stable weight and LBM in both groups.
Taylor et al. 2010
Open-label, single arm.
Patients with metastatic cancer (various tumour types) and weight loss.
1.5 g marine phospholipids per day (1.1 g EPA, 1.7g DHA). Average 94% of prescribed dose taken.
Weight, appetite, pain, BIA parameters, QOL, routine blood parameters including CRP, cytokines (IL-1, IL-6, TNF-α, lyso-PC, lipoprotein profiles, FA profiles of plasma PL, RBCs, MNL.
Increased HDL, IL-6, TNF-α. No change in BIA parameters. Decrease in AA as % total FA in RBC. Increase in DHA (% total FA) in plasma PL. Increase in DHA in RBC and MNL. Decrease in n6/n3 ratio in plasma PL and MNL. Positive correlation between EPA and weight in plasma PL and RBC. Improved QOL and appetite scores.
Abbreviations: EPA, eicosapentaenoic acid; MAMC, mid-arm muscle circumference; TSF, triceps skin fold; TBW, total body water; PL, phospholipid; FA: fatty acid; CRP, C-reactive protein; DHA, docosahexaenoic acid; AA, arachidonic acid; APP, acute phase proteins; PIF, proteolysis inducing factor; APR, acute phase response; BMI, body mass index; PUFA, polyunsaturated fatty acid; QOL, quality of life; LBM, lean body mass; BIA, bioelectrical impedance analysis; RBC, red blood cells; MNL, mononuclear leukocytes; HDL, high density lipoprotein.
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Table A8-2. Summary of studies of fish oil supplementation in patients receiving anti-cancer therapy Study Design Population Intervention Outcomes Results
Bruera et al. 2003
Randomized, double-blinded, controlled (x 2 weeks), followed by open-label (up to 90 days).
Patients with advanced cancer (locally recurrent or metastatic), various tumour types, with decreased appetite and weight loss. 30 in intervention (I), 30 in control (C) group. Chemotherapy and hormonal therapy permitted.
I: 6-18 capsules with 1000 mg fish oil (180 mg EPA, 120 mg DHA). C: 6-18 capsules with 1000 mg olive oil. Mean intake of 9.8 capsules/d (I), and 9.2 capsules/d (C).
No change in symptoms, dietary intake, functional status. No correlation between fish oil dose and anthropometric variables.
Jatoi et al. 2004
Randomized, double-blinded, three study arms.
Patients with incurable cancer (except brain, breast, ovarian, prostate, or endometrial) with weight loss and poor dietary intake. 141 in EPA-treated (EPA), 140 in Megestrol acetate (MA) and 140 in combination (MA+EPA) group. Chemotherapy or radiation treatment permitted.
EPA: EPA nutrition supplement (1.09 g EPA, 0.46 g DHA) twice daily + placebo. 2. MA: Megestrol acetate (MA) 600 mg/d plus isocaloric, isonitrogenous supplement twice daily. Combination: MA + EPA nutrition supplement.
Weight (10% gain above baseline), appetite, survival, QOL, toxicity.
Great % of patients achieved 10% weight gain in MA vs. EPA group. Greater appetite stimulation in MA vs. EPA group when measured by FAACT tool. No difference in survival, QOL, and toxicity between the three treatment arms.
Bauer and Capra. 2005
Open label, single arm.
Pancreatic cancer and NSCLC patients with weight loss, receiving gemcitabine-based chemotherapy (n=8).
Weekly counselling by RD and at least one can per day of n-3 FA enriched nutrition supplement (1.1 g EPA). Mean intake of 1.06 g/d of EPA at week 4 and 1.36 g/d at week 8.
Dietary intake, body composition (LBM), nutritional status (PG-SGA score), performance status, QOL.
Increased total protein, energy, and fibre intake per day, PG-SGA score, performance status, and QOL. Change in nutritional status associated with QOL, performance status, and LBM.
Murphy et al. 2011a
Open-label, controlled.
Newly referred patients with NSCLC receiving first-line treatment with platinum-based doublet chemotherapy. 16 in intervention (I) and 24 in
I: 4 capsules per day (2.2 g EPA, 240 mg DHA) or 7.5 ml fish oil per day (2.2 g EPA, 500 mg DHA). C: No intervention.
I: Weight maintenance, maintenance or gain in muscle mass (69%). C: Weight loss, maintenance of muscle mass (29%). No difference in adipose between groups. No difference in treatment response. Positive association between
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Table A8-2. Summary of studies of fish oil supplementation in patients receiving anti-cancer therapy Study Design Population Intervention Outcomes Results
control (C) group. plasma EPA and rate of muscle change. Murphy et al. 2011b
Open-label, controlled.
Advanced NSCLC patients (stage IIIB or IV) receiving first-line treatment with platinum-based doublet chemotherapy. 15 in intervention (I) and 31 in control (C) group.
I: 4 capsules per day (2.2 g EPA, 240 mg DHA) or 7.5 ml fish oil per day (2.2 g EPA, 500 mg DHA). C: No intervention. Mean intake of 2.1 g EPA per day.
Greater chemotherapy response in I vs. C group. EPA concentration significant independent predictor of chemotherapy response. Greater number of patients completing planned chemotherapy in I vs. C group. No difference in chemotherapy toxicity. Increased survival in I group but not significant.
Read et al. 2007
Open-label, single arm
23 patients with advanced colorectal cancer (Stage IV) on 2nd line chemotherapy with folinic acid, 5-fluorouracil, and irinotecan.
2 tetrapaks per day (240 ml, 1.09 g EPA, 0.46 g DHA each) nutrition supplement containing EPA + RD counselling. Mean intake of 1.7 tetrapaks per day.
Weight, body composition, CRP, QOL, dietary intake, plasma PL, cytokines.
Increased weight, maintenance of LBM. No change in QOL. Increased EPA, increase in CRP but returned to baseline by end of 9-week trial. Correlation between IL-6 and IL-10 and survival, and IL-12 and toxicity.
Silva et al. 2012
Randomized, controlled.
23 patients with colorectal cancer starting chemotherapy. 11 in intervention (I) and 12 in the control (C) group.
I: 4 capsules of fish oil supplement (600 mg EPA+DHA). C: No intervention. Mean intake not reported.
Weight, BMI, cytokines, CRP, albumin.
I: No change in weight and BMI. Decreased CRP, decreased CRP/albumin ratio. C: Decreased weight and BMI. No change in CRP.
Mocellin et al. 2013
Randomized, controlled.
11 patients with colorectal cancer starting chemotherapy. Chemotherapy drugs used alone or in combination: xeloda, oxaliplatin, 5-fluorouracil, leucovorin. 6 in intervention (I), and 5 in control (C) group.
I: Four capsules fish oil per day (90 mg EPA, 60 mg DHA per capsule), C: No intervention. Mean intake not reported.
I: Decreased CRP, CRP/albumin ratio. Increased EPA, DHA. Decreased AA, and n6/n3 ratio. C: Increased CRP, CRP/albumin ratio, n6/n3 ratio. No change in weight, BMI, body composition in either group.
Abbreviations: EPA, eicosapentaenoic acid; DHA, docosahexaenoic acid; BIA, bioelectrical impedance analysis; MAC, mid-arm circumference; TSF, triceps skin fold; PL, phospholipid; FA, fatty acid; QOL, quality of life; FAACT, function assessment of anorexia/cachexia therapy; NSCLC, non-small cell lung cancer; RD, Registered Dietitian; LBM, lean body mass; PG-SGA, patient-generated subjective global assessment; CRP, C-reactive protein; BMI, body mass index; AA, arachidonic acid.
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Appendix 8.2 Consent form
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Appendix 8.3 Research poster
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Appendix 8.4 Sensitivity Analysis In this appendix, we repeat multivariate analysis using linear mixed effects models as previously described with the exclusion of patients with self-reported use of fish or flax oil (n=8).
Table A8-3. Multivariate model for weight – all patients
Variable
β SE
p (Intercept) 74.91 3.13 Time (visit) -0.32 0.18 0.08 Sex1 -10.82 4.62 0.03 Plasma DHA -0.05 0.02 p < 0.01 Plasma Total n-3 0.02 0.01 p < 0.01
1 Male = reference
Table A8-4. Multivariate model for FSA fat free mass – all patients
Variable
β SE
p (Intercept) 54.16 1.58 Time (visit) 0.08 0.11 0.43 Sex1 -13.86 2.37 p < 0.001 Il-6 0.05 0.01 p < 0.01
1 Male = reference
Table A8-5. Multivariate model for BIA fat free mass – all patients
Variable
β SE
p (Intercept) 58.76 1.78 Time (visit) 0.07 0.09 0.40 Sex1 -15.67 2.62 p < 0.001 Il-6 0.04 0.01 p < 0.001 TNF-α 0.07 0.04 0.06 Plasma AA -0.01 0.004 p < 0.01 Plasma Total n-6 0.004 0.001 p < 0.01
1 Male = reference
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Table A8-6. Multivariate model for PG-SGA score – all patients
Variable
β SE
p (Intercept) 16.85 2.63 Time (visit) -0.06 0.31 0.86 Diagnosis1 -5.60 1.61 p < 0.01 Protein intake (g/day) -0.04 0.02 0.02 Il-6 0.08 0.04 0.03 Plasma Total n-3 -0.01 0.006 0.06
1 Gastric cancer = reference
Table A8-7. Multivariate model for weight with tumour interaction
Variable
β SE
p (Intercept) 78.18 4.23 Time (visit) 0.24 0.23 0.31 Sex1 -11.72 4.56 0.02 Tumour presence2 -4.56 4.61 0.33 Plasma DHA -0.05 -0.02 p < 0.01 Plasma Total n-3 0.02 0.01 p < 0.01 Time*Tumour presence -0.97 0.27 p < 0.001
1 Male = reference 2 Resected = reference
Table A8-8. Multivariate model for FSA fat free mass with tumour interaction
Variable
β SE
p (Intercept) 55.32 2.19 Time (visit) 0.25 0.15 0.09 Tumour presence1 -1.62 2.46 0.51 Sex2 -14.16 2.39 p < 0.001 Il-6 0.04 0.02 p < 0.01 Time*Tumour presence -0.34 0.21 0.11
1 Resected = reference 2 Male = reference
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Table A8-10. Multivariate model for PG-SGA score with tumour interaction
Variable
β SE
p (Intercept) 17.40 3.11 Visit 0.29 0.43 0.51 Tumour presence1 0.78 2.31 0.74 Diagnosis2 -5.85 1.83 p < 0.01 Protein intake (g/d) -0.04 0.02 0.02 Il-6 0.07 0.04 0.06 Plasma Total n-3 -0.01 0.006 0.04 Time*Tumour presence -0.64 0.58 0.27
1 Resected = reference 2 Gastric cancer = reference
Table A8-9. Multivariate model for BIA fat free mass with tumour interaction
Variable
β SE
p (Intercept) 60.40 2.43 Time (visit) 0.23 0.12 0.06 Tumour presence1 -2.22 2.66 0.41 Sex2 -16.17 2.63 p < 0.001 Il-6 0.04 0.01 p < 0.01 TNF-α 0.06 0.04 0.11 Plasma AA -0.013 0.004 p < 0.01 Plasma Total n-6 0.004 0.001 p < 0.01 Time*Tumour presence -0.312 0.168 0.07