Lynch syndrome screening in gynaecological cancers: results of an international survey with recommendations for uniform reporting terminology for mismatch repair immunohistochemistry results
Bibliographic record
Abstract
AIMS: Lynch syndrome (LS) is associated with an increased risk of developing endometrial carcinoma (EC) and ovarian carcinoma (OC). There is considerable variability in current practices and opinions related to screening of newly diagnosed patients with EC/OC for LS. An online survey was undertaken to explore the extent of these differences. METHODS AND RESULTS: An online questionnaire was developed by a panel of experts and sent to all members of the British Association of Gynaecological Pathologists (BAGP) and the International Society of Gynecological Pathologists (ISGyP). Anonymised results were received and analysed. Thirty-six BAGP and 44 ISGyP members completed the survey. More than 90% of respondents were aware of the association of LS with both EC and OC, but 34% were not aware of specific guidelines for LS screening. Seventy-one per cent of respondents agreed that universal screening for LS should be carried out in all newly diagnosed EC cases, with immunohistochemistry (IHC) alone as the preferred approach. Only 36% of respondents currently performed IHC or microsatellite instability testing on all newly diagnosed EC cases, with most of the remaining respondents practising selective screening, based on clinical or pathological features or both. A significant minority of respondents (35%) believed that patient consent was required before performance of mismatch repair (MMR) protein IHC. Almost all respondents favoured the use of standardised terminology for reporting MMR protein staining results, and this is proposed herein. CONCLUSION: There is wide support for universal LS screening in patients with EC, but this survey highlights areas of considerable variation in practice.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".