Comparison of Inhibin A Immunoassays: Recommendation for Adoption of Standardized Reporting
Bibliographic record
Abstract
Serum inhibin A measurements have become increasingly common in clinical use, and their inclusion in prenatal screening for Down syndrome has been recently advocated. Two methods are commercially available for the specific measurement of dimeric inhibin A in human serum or plasma (1). Given the absence of a gold standard and the evolving clinical utility of inhibin A, a detailed comparison of the two inhibin A ELISAs is warranted. In the studies reported here, we undertook the evaluation of these methods and a direct comparison of their performance. The results obtained support the use of both methods and provide a basis for comparing values across these methods. Furthermore, we recommend that laboratories adopt a reporting unit of IU/mL based on the recombinant human Inhibin A International Reference Preparation (IRP) distributed by the National Institute for Biological Standards and Control on behalf of the WHO (91/624). Inhibin A is a dimeric glycoprotein hormone belonging to the transforming growth factor-β superfamily of cytokines. In addition to its numerous local, tissue-specific regulatory or “cytokine-type” actions (2)(3)(4), ovary-produced inhibin A is an important negative feedback hormone that suppresses pituitary secretion of follicle-stimulating hormone during the late follicular and luteal phases of the menstrual cycle (5)(6). Furthermore, circulating concentrations of inhibin A appear to reflect tumor mass for certain forms of ovarian cancer (7), particularly granulosa cell adenocarcinomas, and measurement of inhibin A also may be useful in assessment of gestational trophoblastic disease (8)(9). In addition, the measurement of serum inhibin A has recently been demonstrated as useful in the clinical setting as part of the “quadruple” antenatal screen for Down syndrome (10)(11)(12).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.449 | 0.576 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.016 | 0.019 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.020 | 0.007 |
| Research integrity | 0.015 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".