3.3 Sample Types, Clinical Context & Predictive Metrics
Key Takeaways
- Sample type (blood, saliva/buccal, cultured cells, tissue, CVS, amniocytes) affects DNA quality, culture success, mosaicism representation, and which cytogenetic vs molecular assays are feasible.
- Sensitivity and specificity describe intrinsic test performance; PPV and NPV additionally depend on pretest probability (prevalence or clinical prior).
- Analytic validity, clinical validity, and clinical utility are distinct layers—passing lab QC does not automatically mean the result improves patient outcomes.
- High sensitivity is necessary but not sufficient for population screening; PPV collapses when prevalence is low even if specificity looks “high.”
- Counseling must translate metrics into decisions: what a negative result rules out, what residual risk remains, and whether the sample can even support the ordered test.
Clinical context drives both sample and metric interpretation
A perfect assay on the wrong specimen—or a highly sensitive screen in a low-prevalence population—still produces counseling failures. Domain 3A links test methodologies to sample type, clinical context, and predictive value. You must know what each specimen can support and how to move fluently among sensitivity, specificity, PPV, NPV, and the validity/utility triad.
Sample types and practical considerations
| Sample | Typical uses | Counsel / logistics notes |
|---|---|---|
| Peripheral blood | Karyotype, CMA, most molecular sequencing | Standard for constitutional testing; reflects leukocyte lineage—may miss tissue-limited mosaicism |
| Saliva / buccal | Many molecular assays | Convenient; DNA yield/quality variable; eating, smoking, bacterial DNA can affect QC; confirm lab acceptance |
| Cultured fibroblasts / other tissue | Suspected mosaicism; culture-dependent cytogenetics | Invasive relative to blood; chosen when blood may not represent the relevant tissue |
| CVS (chorionic villi) | Prenatal diagnosis | Placental lineage; mosaicism/CPM issues detailed in prenatal chapters—flag that placenta ≠ always fetus |
| Amniotic fluid / amniocytes | Prenatal diagnosis | Fetal cell source after culture or direct methods; procedure-risk counseling is separate from lab methodology |
| Products of conception / fetal tissue | Pregnancy loss workup | Tissue quality and maternal cell contamination matter for interpretation |
| Tumor / somatic tissue | Somatic variant profiling | Not a substitute for germline testing; germline confirmation may need blood/saliva |
Sample–method matching traps
- Ordering a karyotype when only saliva DNA was collected without confirming the lab can culture or whether a DNA-based alternative is intended.
- Interpreting a normal blood genetic test as excluding mosaic disease confined to other tissues.
- Treating CVS results as identical to amniocentesis without acknowledging placental mosaicism risk (full CPM algorithms belong in prenatal diagnostic content).
- Using tumor NGS reports as definitive germline results without orthogonal germline specimen testing when hereditary risk is in question.
Preanalytical realities worth saying out loud
Ship time, heparin vs EDTA tubes for different assays, maternal cell contamination in prenatal samples, and failed cultures all change turnaround and sometimes force a redraw. Pretest counseling should include the possibility of quantity/quality insufficient (QNS) results.
Sensitivity, specificity, PPV, and NPV
Memorize definitions, then practice how prevalence moves predictive values.
| Metric | Definition | Formula intuition |
|---|---|---|
| Sensitivity | Among people with the condition (or target variant/class), the proportion who test positive | True positives / (true positives + false negatives) |
| Specificity | Among people without the condition, the proportion who test negative | True negatives / (true negatives + false positives) |
| Positive predictive value (PPV) | Among people who test positive, the proportion who truly have the condition | True positives / (true positives + false positives) |
| Negative predictive value (NPV) | Among people who test negative, the proportion who truly do not have the condition | True negatives / (true negatives + false negatives) |
The prevalence dependence rule
Sensitivity and specificity are properties of the test in a defined comparison (with caveats about spectrum bias). PPV and NPV depend on pretest probability (disease prevalence in the tested population or individualized clinical prior).
| If prevalence falls… | What happens |
|---|---|
| Same sensitivity & specificity | PPV decreases (more of the positives are false positives) |
| Same sensitivity & specificity | NPV increases (negatives are more likely truly negative) |
This is why a screening test with 99% specificity can still yield a modest PPV in a rare condition: false positives from the huge unaffected population can outnumber true positives.
Worked conceptual example (screening intuition)
Imagine a condition with prevalence 1/1,000 in a screened population and a test with 99% sensitivity and 99% specificity.
- In 100,000 people: ~100 affected; ~99 true positives; ~1 false negative.
- ~99,900 unaffected; at 99% specificity → ~999 false positives.
- PPV ≈ 99 / (99 + 999) ≈ 9%.
Families hear “99% accurate” and imagine a 99% PPV. Your counseling job is to separate sensitivity/specificity language from predictive value after a positive screen, then offer diagnostic confirmation pathways.
Diagnostic vs screening context
| Context | Prior | Metric emphasis |
|---|---|---|
| High-suspicion diagnostic testing | High pretest probability | NPV of a negative may still leave residual risk if sensitivity <100%; PPV of a well-targeted test is often higher |
| Population screening | Low prevalence | Even excellent specificity can yield limited PPV; confirm positives |
| Cascade testing for a known familial variant | Prior depends on relatedness/Mendelian risk | Site-specific testing performance differs from population screens |
Analytic validity, clinical validity, clinical utility
These three layers appear throughout genetic testing policy and Domain 3A reasoning:
| Layer | Question it answers | Example |
|---|---|---|
| Analytic validity | Does the lab assay accurately and reliably detect the analyte/variant it claims to detect? | Does the NGS pipeline call this SNV with confirmed accuracy and reproducibility? |
| Clinical validity | How well does the test result relate to the presence/absence/risk of the clinical phenotype or disease? | Does a pathogenic variant in this gene actually associate with the syndrome with known penetrance? |
| Clinical utility | Does using the test improve outcomes, decisions, or care meaningfully (diagnosis, management, prevention, reproductive options)? | Does identifying the variant change surveillance, therapy eligibility, or reproductive planning? |
Exam-ready distinctions:
- A test can be analytically valid yet have weak clinical validity if the gene–disease relationship is uncertain (interpretation problem).
- A result can be clinically valid yet have limited clinical utility today if no management change or decision follows (still may have personal utility for some patients—counsel explicitly).
- VUS results often reflect limited clinical validity for that specific variant even when the assay analytically sequenced the base correctly.
Putting sample, method, and metrics together
- Confirm the specimen can support the method (culture vs DNA; prenatal source limitations).
- State what positive and negative mean using sensitivity/specificity, then translate to PPV/NPV using the patient’s pretest probability.
- Avoid promising “ruled out” when sensitivity is incomplete or the sample might not represent mosaic tissue.
- Separate lab accuracy (analytic validity) from disease meaning (clinical validity) and actionability (clinical utility).
- For screens, plan the confirmatory diagnostic step before disclosing a low-PPV positive as if it were a diagnosis.
Mastering this section prevents the most common Domain 3 counseling error: treating every laboratory adjective—“sensitive,” “comprehensive,” “normal”—as if it carried the same predictive meaning in every clinical context.
A screening test has fixed sensitivity and specificity. If the condition’s prevalence in the screened population decreases, what happens to positive predictive value (PPV)?
Which definition correctly matches specificity?
A patient has a tumor NGS report with a variant in a hereditary cancer gene. What is the most accurate counseling point about sample type?
Which statement best distinguishes clinical utility from analytic validity?