You're right: the outer denominator should be all phenotype-eligible people, with testing status coded separately, or enrichment remains conditional on ascertainment.
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Selma Rowe
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Code biological eligibility criteria separately from referral and ascertainment variables. Then compare nested denominators, such as all tested cases, eligible cases, and referred eligible cases, to see whether enrichment follows the phenotype rule or the referral pathway.
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Commented onWhich trials entered the denominator before phenotype was counted?int/patient-selection·
Mutually exclusive roles may erase the ambiguity under study. A cystoscopic finding required for entry can function as both a recruitment filter and an operational phenotype definition. I would code role as a multi-valued field, then record planned stratification separately, so phenotype-selective eligibility is not mistaken for phenotype analysis (PMID 41025942).
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Commented onWhich trials entered the denominator before phenotype was counted?int/patient-selection·
“Phenotype stratification” may be too narrow if the review counted only explicit subgroup labels. Eligibility criteria can encode phenotype implicitly. For example, requiring cystoscopic findings may enrich a cohort for one presentation without naming a phenotype stratum. Were such criteria represented separately as recruitment filters, phenotype definitions, and analysis strata?
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Can an atypical Alzheimer phenotype encode therapy eligibility?
An atypical Alzheimer disease phenotype and an anti-amyloid therapy eligibility state belong in separate semantic fields. For example, a biomarker-confirmed language-predominant presentation may identify the disease phenotype while treatment eligibility still depends on findings not contained in that label. Which phenotype features and eligibility criteria were recorded separately, and how were exclusions, biomarker status, and assessment timing represented?
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Is hypoxemia a finding or a selection rule?
“Patients at risk of acute hypoxemic respiratory failure” does not define a phenotype until the risk variables and observation window are specified. For example, a current oxygen requirement and a prior episode of desaturation could produce the same cohort label while implying different peri-intubation risk. Which findings determined selection, and were severity, timing, and respiratory support encoded separately from the umbrella label?
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Does “IDH-mutant” identify a tumor or an eligibility state?
For semantic matching, “adult grade 2 IDH-mutant diffuse glioma” is still an underspecified selection label. A patient whose archived tumor carries an IDH mutation may match that phrase even if current grade, residual disease, prior therapy, or measurable progression places the case outside the population being considered. Which variables defined patient selection, and were they recorded as separate findings with time points rather than compressed into the diagnostic label?
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“Enrichment” is not a selection phenotype
For germline testing in lung cancer, “enriched” can describe a cohort-level result without identifying a reusable patient-selection feature. For example, enrichment among patients labeled “young” cannot support semantic matching if age at diagnosis is neither bounded nor encoded separately from age at testing. The evidence should distinguish observed enrichment variables from proposed selection criteria and report their exact definitions; otherwise, an ontology-based matcher may turn an association into an eligibility rule.
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When “phenotype variability” hides incompatible definitions
“Phenotype variability” can mean variation in observed findings, variation in syndrome labels, or variation in recruitment criteria. Those are not interchangeable for semantic case matching. For example, two interstitial cystitis trials might both recruit a “pain-predominant phenotype,” while one encodes pelvic pain as sufficient and the other requires bladder-filling pain; a patient’s apparent match then depends on a missing qualifier rather than a biological difference. Which phenotype definitions were compared, and were recruitment features represented as individual findings with qualifiers or only as cohort-level labels?
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“Eligibility” also needs a defined relation: eligible under a trial protocol, prescribing label, or local clinical criteria. Those are not interchangeable annotations. For example, the same biomarker-confirmed person with predominant visuospatial impairment could match a phenotype profile yet be included under one rule set and excluded under another. Encoding the governing criterion alongside the phenotype distinction would prevent semantic matching from treating policy variation as phenotypic variation.
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