Interpretation of Laboratory Tests: A Case-Oriented Review of Clinical Laboratory Diagnosis (Part 2) Roger L. Bertholf, Ph.D. Associate Professor of Pathology University of Florida Health Science Center/Jacksonville Mark A. Bowman, MT(ASCP), Ph.D. Associate Professor of Clinical Pathology Clinical Laboratory Sciences Program Director University of Iowa College of Medicine
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Interpretation of Laboratory Tests: A Case-Oriented Review of Clinical Laboratory Diagnosis (Part 2) Roger L. Bertholf, Ph.D. Associate Professor of Pathology.
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Interpretation of Laboratory Tests:A Case-Oriented Review of Clinical
Laboratory Diagnosis (Part 2)
Interpretation of Laboratory Tests:A Case-Oriented Review of Clinical
Laboratory Diagnosis (Part 2)
Roger L. Bertholf, Ph.D.Associate Professor of Pathology
University of Florida Health Science Center/Jacksonville
Mark A. Bowman, MT(ASCP), Ph.D.Associate Professor of Clinical Pathology
Clinical Laboratory Sciences Program Director
University of Iowa College of Medicine
Roger L. Bertholf, Ph.D.Associate Professor of Pathology
University of Florida Health Science Center/Jacksonville
Mark A. Bowman, MT(ASCP), Ph.D.Associate Professor of Clinical Pathology
Clinical Laboratory Sciences Program Director
University of Iowa College of Medicine
Case 1: Failure to ConceiveCase 1: Failure to Conceive
Case HistoryCase History
A couple visits their family doctor, complaining that the wife had been unable to become pregnant.
What questions should you ask?
A couple visits their family doctor, complaining that the wife had been unable to become pregnant.
What questions should you ask?
InfertilityInfertility
• Definition: One year of unprotected intercourse without pregnancy– 1°: No previous pregnancies
– 2°: Previous pregnancy (not necessarily live birth)
• Fecundability: Probability of achieving pregnancy within a menstrual cycle– 20-25% for normally fertile couples 90% of couples should conceive within one year
• 10-15% of couples experience infertility
• Definition: One year of unprotected intercourse without pregnancy– 1°: No previous pregnancies
– 2°: Previous pregnancy (not necessarily live birth)
• Fecundability: Probability of achieving pregnancy within a menstrual cycle– 20-25% for normally fertile couples 90% of couples should conceive within one year
• 10-15% of couples experience infertility
Probabilities of failure to conceiveProbabilities of failure to conceive
10
100
0 2 4 6 8 10 12
Months of unprotected intercourse
Per
cent
fai
led
Nulliparous
Parous
5 months
2.7 months
50
Requirements for conceptionRequirements for conception• Male must produce adequate numbers of normal, motile
spermatozoa• Male must be capable of ejaculating the sperm through a
patent ductal system• The sperm must be able to traverse an unobstructed
female reproductive tract• The female must ovulate and release an ovum• The sperm must be able to fertilize the ovum• The fertilized ovum must be capable of developing and
implanting in appropriately prepared endometrium
• Male must produce adequate numbers of normal, motile spermatozoa
• Male must be capable of ejaculating the sperm through a patent ductal system
• The sperm must be able to traverse an unobstructed female reproductive tract
• The female must ovulate and release an ovum• The sperm must be able to fertilize the ovum• The fertilized ovum must be capable of developing and
implanting in appropriately prepared endometrium
Sperm MorphologySperm Morphology
• % normal spermatozoa
• Head, acrosomal region
• Vacuoles
• Midpiece abnormalities
• Tail defects
• % normal spermatozoa
• Head, acrosomal region
• Vacuoles
• Midpiece abnormalities
• Tail defects
Comparison of CriteriaComparison of Criteria
WHO (1987)
WHO (1992)
Strict (1986)
% Normal 50 30 14
Head length (m) 3.0-5.0 4.0-5.5 5.0-6.0
Head width (m) 2.0-3.0 2.5-3.5 2.5-3.5
W/L 1.5-2.0 1.5-1.75 1.0-1.67
Evaluation of semenEvaluation of semen
• 2-3 days abstinence prior to collection
• Gelation/liquefaction (macroscopic)
• Color/volume/consistency/pH
• 2-3 days abstinence prior to collection
• Gelation/liquefaction (macroscopic)
• Color/volume/consistency/pH
Sperm morphologySperm morphology
Sperm motilitySperm motility
The Endocrine SystemThe Endocrine System
Hypothalamus/Pituitary/Pineal
Thyroid/Parathyroid
ThymusAdrenalPancreas
Kidney
Testis
Ovary
Evaluation of male infertilityEvaluation of male infertility
H&P
Follow-upSemen analysis
PCTAntisperm antibodies
Sperm mucuous penetration
Repeat
LH, FSH, Testosterone
N A
N
N
A
A
Male Hypothalamic-Pituitary-Gonadal Axis
Male Hypothalamic-Pituitary-Gonadal Axis
GnRH
LH, FSH
TestosteroneInhibin
FSH acts on Sertoli cellsLH acts on Leydig cells
Male reproductive endocrinologyMale reproductive endocrinology
LH FSH Testosterone Diagnosis
Hypothalamic or pituitary failure
Gonadal failure
N N Germinal compartment failure
N N or Androgen resistence
N N N Idiopathic
Causes of female infertilityCauses of female infertility
• 1955: Rumke and Hellinga demonstrate association between humoral autoantibodies to sperm and unexplained infertility– Results were controversial, and hampered by
inadequate analytical techniques– Humoral antibodies do not effect fertility
unless they exist in the reproductive tract
• Antibodies must be demonstrated on the sperm surface
• 1955: Rumke and Hellinga demonstrate association between humoral autoantibodies to sperm and unexplained infertility– Results were controversial, and hampered by
inadequate analytical techniques– Humoral antibodies do not effect fertility
unless they exist in the reproductive tract
• Antibodies must be demonstrated on the sperm surface
Effect of sperm autoantibodiesEffect of sperm autoantibodies
so membrane attack occurs in the female reproductive tract
Anti-sperm antibodies in the femaleAnti-sperm antibodies in the female
• Clinically significant only in high titers (in serum)
• Anti-sperm antibodies may exist in vaginal secretions or cervical mucus even when humoral antibodies are not detected
• Clinically significant only in high titers (in serum)
• Anti-sperm antibodies may exist in vaginal secretions or cervical mucus even when humoral antibodies are not detected
Diagnosis of immune-related infertility
Diagnosis of immune-related infertility
• Post-coital test– Evaluates sperm viability in the cervical mucus
• Humoral antibodies– Not diagnostic
• Demonstration of antibodies on the sperm surface
• Post-coital test– Evaluates sperm viability in the cervical mucus
• Humoral antibodies– Not diagnostic
• Demonstration of antibodies on the sperm surface
Case 3: Unexplained Weight LossCase 3: Unexplained Weight Loss
Case HistoryCase History
A 62 year old man visited his family doctor because of weight loss from 185 lbs. to 163 lbs. The patient was not obese prior to his weight loss, and he described his appetite as “normal.” He had occasional indigestion. The patient was afebrile, and vital signs were normal. The patient had normal bowel movements.
What other questions would you ask this patient?
A 62 year old man visited his family doctor because of weight loss from 185 lbs. to 163 lbs. The patient was not obese prior to his weight loss, and he described his appetite as “normal.” He had occasional indigestion. The patient was afebrile, and vital signs were normal. The patient had normal bowel movements.
What other questions would you ask this patient?
Pre-testPre-test
• What are “tumor markers”?
• What are desirable characteristics of a tumor marker?
• In what ways are tumor markers used?
• What are “tumor markers”?
• What are desirable characteristics of a tumor marker?
• In what ways are tumor markers used?
Leading causes of death in the United States
Total Deaths Percent of total
All causes 2.391,399 100
Cardiovascular disease 725,192 30.3
Cancer 539,838 23.0
Cerebrovascular 167,366 7.0
COPD 124,181 5.2
Accidents 97,860 4.1
Source: National Vital Statistics Report (1999 data)
Types of tumor markersTypes of tumor markers
• Enzymes and isoenzymes
• Hormones
• Oncofetal antigens
• Carbohydrate antigens
• Receptors
• Oncogene products
• Genetic markers
• Enzymes and isoenzymes
• Hormones
• Oncofetal antigens
• Carbohydrate antigens
• Receptors
• Oncogene products
• Genetic markers
Desirable characteristics of tumor markers
Desirable characteristics of tumor markers
• Easy to measure
• Specific for tumor
• Always present with tumor
• Easy to measure
• Specific for tumor
• Always present with tumor
Sensitivity vs. SpecificitySensitivity vs. Specificity
• Sensitivity and specificity are inversely related.
Mar
ker
con
cen
trat
ion
- +Disease
Sensitivity vs. SpecificitySensitivity vs. Specificity
• Sensitivity and specificity are inversely related.
• How do we determine the best compromise between sensitivity and specificity?
Receiver Operating Characteristic
Receiver Operating Characteristic
Tru
e p
osi
tive
rat
e(s
ensi
tivi
ty)
False positive rate1-specificity
Evaluating the clinical performance of laboratory tests
Evaluating the clinical performance of laboratory tests
• The sensitivity of a test indicates the likelihood that it will be positive when disease is present
• The specificity of a test indicates the likelihood that it will be negative when disease is absent
• The predictive value of a test indicates the probability that the test result, positive or negative, correctly classifies a patient
Predictive ValuePredictive Value
The predictive value of a clinical laboratory test takes into account the prevalence of a certain disease, to quantify the probability that a positive test is associated with the disease in a randomly-selected individual, or alternatively, that a negative test is associated with health.
IllustrationIllustration• Suppose you have a new marker for liver
cancer
• The test correctly identified 98 of 100 patients with confirmed liver cancer (What is the sensitivity?)
• The test was positive in 15 of 100 patients with no evidence of liver cancer (What is the specificity?)
Test performanceTest performance
• The sensitivity is 98.0%
• The specificity is 85%
• Liver cancer has an incidence of 1.5:100,000
• What happens if we screen 1 million people?
AnalysisAnalysis
• In 1 million people, there will be 15 cases of liver cancer.
• Our test will (most likely) identify all of these cases (TP)
• Of the 999,985 healthy subjects, the test will be positive in 15%, or about 150,000 (FP).
Predictive value of the positive test
Predictive value of the positive test
The predictive value is the % of all positives that are true positives:
%01.0
100000,15015
15
100
FPTP
TPPV
What about the negative predictive value?
What about the negative predictive value?
• TN = 849,985
• FN = 0
%100
1000985,849
985,849
100
FNTN
TNPV
Summary of predictive valueSummary of predictive value
Predictive value describes the usefulness of a clinical laboratory test in the real world.
Or does it?
Lessons about predictive valueLessons about predictive value
• Even when you have a very good test, it is generally not cost effective to screen for diseases which have low incidence in the general population. Exception?
• The higher the clinical suspicion, the better the predictive value of the test. Why?