Validation of cell‐based fluorescence assays: practice guidelines from the ICSH and ICCS – part II – preanalytical issues
Bibliographic record
Abstract
Flow cytometry and other technologies of cell-based fluorescence assays are as a matter of good laboratory practice required to validate all assays, which when in clinical practice may pass through regulatory review processes using criteria often defined with a soluble analyte in plasma or serum samples in mind. Recently the U.S. Food and Drug Administration (FDA) has entered into a public dialogue in the U.S. regarding their regulatory interest in laboratory developed tests (LDTs) or so-called "home brew" assays performed in clinical laboratories. The absence of well-defined guidelines for validation of cell-based assays using fluorescence detection has thus become a subject of concern for the International Council for Standardization of Haematology (ICSH) and International Clinical Cytometry Society (ICCS). Accordingly, a group of over 40 international experts in the areas of test development, test validation, and clinical practice of a variety of assay types using flow cytometry and/or morphologic image analysis were invited to develop a set of practical guidelines useful to in vitro diagnostic (IVD) innovators, clinical laboratories, regulatory scientists, and laboratory inspectors. The focus of the group was restricted to fluorescence reporter reagents, although some common principles are shared by immunohistochemistry or immunocytochemistry techniques and noted where appropriate. The work product of this two year effort is the content of this special issue of this journal, which is published as 5 separate articles, this being Validation of Cell-based Fluorescence Assays: Practice Guidelines from the ICSH and ICCS - Part II - Preanalytical issues. © 2013 International Clinical Cytometry Society.
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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 | 0.165 | 0.145 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.012 | 0.006 |
| Research integrity | 0.013 | 0.012 |
| Insufficient payload (model declined to judge) | 0.002 | 0.008 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".