Prevalence of germline mutations in pancreatic carcinoma patients (PCP) unselected for family history (FH).
Bibliographic record
Abstract
e16263 Background: Despite being one of the deadliest tumors worldwide, hereditary factors involved in PC are not fully understood. Thus, our objective is to assess the prevalence of germline mutations in PC cohorts not selected for FH. Methods: A systematic review was performed, using the descriptors related to PC and germline mutations, employing Pubmed, Lilacs, Web of Science and Embase, until August/2020. Three investigators were involved in reviewing titles and abstracts by peers. Exclusions comprehended articles of non-English language, studies investigating endocrine PC or case-reports. For the present analysis, the inclusion criteria were: original full paper available for data extraction, studies with patients unselected for FH and evaluating a panel of at least 10 genes, WES or WGS. Results from our group evaluating a cohort of PC Brazilian patients were also considered. We present prevalence results for germline mutations in 8 genes, comprehending ATM, BRCA1, BRCA2, CDKN2A, CHEK2, MSH6, PALB2 (the most frequently mutated genes in PC) and FANCM (previously detected in our Brazilian cohort). Results: After exclusion of duplicate titles, 2, 035 titles were available. Using the criteria described above, 23 articles were selected for analysis and involved cohorts from Australia, Canada, USA, Japan, Czech Republic and our Brazilian cohort, totaling 11, 165 PCP evaluated. The predominant histology was adenocarcinoma (15/24 studies), 22/24 studies evaluated a panel of genes and for studies providing demographic data, the mean age of PCP was 64 (13-93) years (n = 8, 000). Six out of eight genes were evaluated in at least 10, 600 patients, among which BRCA2 mutations had the highest prevalence, followed by ATM. Mutations in CHEK2 occupied the third place in prevalence, despite being evaluated in only 74.5% of the entire cohort. BRCA1, PALB2, CDKN2A, MSH6 and FANCM showed a prevalence of less than 1%, according to the table below. Although being infrequent among PCP, it is interesting to observe that an identical FANCM mutation was detected in two unrelated Brazilian patients. Conclusions: Analysis of cohorts unselected for FH indicates that BRCA2, ATM and CHEK2 are the most frequently mutated genes in these PCP. Further studies are needed to better characterize the spectrum and prevalence of mutations in PCP from populations other than Caucasians, especially in miscegenated people.[Table: see text]
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.017 | 0.018 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".