Immunohistochemical Screening of Upper Tract Urothelial Carcinomas for Lynch Syndrome Diagnostics: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: To review the effect of universal screening of newly diagnosed upper tract urothelial carcinomas (UTUC) for mismatch repair (MMR) protein loss to aid in Lynch syndrome diagnostics. MATERIALS AND METHODS: Studies were identified through PubMed on December 1, 2021. Eligibility criteria were universal immunohistochemical analyses for at least 2 MMR proteins in unselected, consecutively collected UTUC cohorts. Exclusion criteria included reviews, case-reports, non-English language, and non-humans. Risk of bias was assessed using a modified Newcastle-Ottawa scale. Meta-analyses were performed to compare the association between clinical criteria and Lynch syndrome diagnoses. RESULTS: From 12 included studies, 1628 surgically removed UTUC from 1626 patients were screened for MMR protein loss. In 11 studies, 140 of the 1559 patients had tumors with loss (9.0%) with 80.7% showing loss of MSH2, MSH6, or both. In 7 studies, genetic testing confirmed Lynch syndrome diagnosis for 20 of 970 patients (2.1%). In 8 studies, 31 patients were given a clinical Lynch syndrome diagnosis (2.6%). In total, 51 assumed or verified Lynch syndrome patients were identified among 1087 patients (4.7%). Meta-analyses of 3 studies showed significant association between previous cancer diagnosis and Lynch syndrome-associated UTUC (P = .038). CONCLUSION: Despite the few studies conducted and lack of genetic testing, current data suggests that universal screening for MMR protein loss in UTUC may result in Lynch syndrome diagnoses in 4.7%. However, for the screening to be effective for Lynch syndrome diagnostics, follow-up investigations, such as genetic testing for MMR variants, are needed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".