Retracted: Immunohistochemical prognostic markers in diffuse large B-cell lymphoma: validation of tissue microarray as a prerequisite for broad clinical applications (a study from the Lunenburg Lymphoma Biomarker Consortium)
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
BACKGROUND AND AIMS: The results of class prediction and the determination of prognostic markers in diffuse large B-cell lymphoma (DLBCL) have been variably reported. Apart from biological variations, this may be caused by differences in laboratory techniques, scoring definitions and inter- and intra-observer variation. In this study, an international collaboration of clinical lymphoma research groups has concentrated on validation and standardisation of immunohistochemistry of the currently potentially interesting prognostic markers in DLBCL. METHODS: Sections of a tissue microarray with 36 cases of DLBCL were stained in eight laboratories with antibodies to CD20, CD5, bcl-2, bcl-6, CD10, HLA-DR, MUM-1 and Ki-67 according to local methods. The study was performed in two rounds, firstly focused on the evaluation of laboratory staining variation, and secondly on the scoring variation. RESULTS: Different techniques resulted in highly variable results and poor reproducibility for almost all markers. Reproducibility of the nuclear markers was highly sensitive to technical variations, including immunological enhancement techniques (agreements 34%). With elimination of variation due to staining and uniformly agreed on scoring criteria, significant improvement was seen; however less so for bcl-6 and Ki-67 (agreement 53-58%). Absence of internal controls that preclude scoring, significantly influenced the results for CD10 and bcl-6. CONCLUSION: Semi-quantitative immunohistochemistry for subclassification of DLBCL is feasible, but with varying rates of concordance for different markers and only using optimised techniques and strict scoring criteria. These findings may explain the wide variation in prognostic impact reported in the literature. Harmonisation of techniques and centralised consensus review appears mandatory when using immunohistochemical biomarkers for treatment stratification.
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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 | 0.049 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".