Using a Family History Questionnaire to Identify Adult Patients with Increased Genetic Risk for Sarcoma
Bibliographic record
Abstract
BACKGROUND: Sarcomas in adults can be associated with hereditary cancer syndromes characterized by early-onset predisposition to numerous types of cancer. Because of variability in familial presentation and the largely unexplained genetic basis of sarcomas, ascertainment of patients for whom a genetics evaluation is most indicated poses challenges. We assessed the utility of a Sarcoma Clinic Genetic Screening (scgs) questionnaire in facilitating that task. METHODS: Between 2008 and 2012, 169 patients (median age: 53 years; range: 17-88 years) completed a self-administered scgs questionnaire. A retrospective chart review was completed for all respondents, and descriptive statistics were reported. Probands were divided into two groups depending on whether they did or did not report a family history of Li-Fraumeni syndrome-type cancers. RESULTS: A family history of cancer (as far as 3rd-degree relatives) was reported in 113 of 163 sarcoma patients (69%). Eeles Li-Fraumeni-like (lfl) criteria were fulfilled in 46 probands (28%), Chompret lfl in 21 (13%), Birch lfl in 8 (5%), and classic Li-Fraumeni in none. In the 10 probands tested for TP53 mutations, 1 pathogenic mutation was found. Further investigation of selected families led to the discovery of germline mutations in MLH1, MSH2, and APC genes in 3 individuals. CONCLUSIONS: The scgs questionnaire was useful for ascertaining probands with sarcoma who could benefit from a genetic assessment. The tool allowed us to identify high-risk families fitting the criteria for lfl and, surprisingly, other hereditary cancer syndromes. Similar questionnaires could be used in other cancer-specific clinics to increase awareness of the genetic component of these cancers.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".