Abstract 4810: Family history of cancers, medical history, and pancreatic cancer risk in the Ontario Pancreatic Cancer Case-Control Study.
Bibliographic record
Abstract
Abstract Background: Pancreatic cancer is one of the most fatal cancers. Given the high mortality burden of this disease, there is a pressing need to determine causes so effective prevention strategies can be implemented. Family history of pancreatic cancer, and medical history of diabetes or chronic pancreatitis have been previously identified as risk factors for pancreatic cancer. However, it is not clear whether other medical conditions or family history of other cancers have a role in pancreatic cancer etiology. Therefore we aim to conduct an in-depth analysis to investigate the association between family history of cancer and medical history with pancreatic cancer risk, in the Ontario Pancreatic Cancer Case-Control Study. Methods: We used data from 743 cases and 656 controls from the Ontario Pancreatic Case-Control Study. Self-administered questionnaires provided information regarding family history of cancer, medical history and other risk factors such as smoking status and BMI. Family history was defined as any biological first-degree relative (parent, sibling or child) with a cancer diagnosis. We analyzed the association by cancer site, and within each site by type and numbers of affected relatives. Medical history of a disease or condition was defined as having the disease or condition two years prior to diagnosis of pancreatic cancer. We also conducted stratified analysis by smoking status and age of onset of pancreatic cancer. Unconditional logistic regression was used to produce odds ratios with 95% confidence limits for all factors of interest.Results: A family history of pancreatic cancer was associated with increased pancreatic cancer risk (OR=1.87 95% CI 1.11-3.16). We also observed an increased risk of pancreatic cancer for individuals with a family history of prostate cancer, with an OR of 1.59 (95% CI = 1.05-2.40). This association was modified by smoking behavior, and was only present among never smokers (OR=2.19, 95% CI 1.25-3.83), not ever smokers (OR=0.98, 95% CI= 0.53-1.82). Diabetes mellitus more than 2 years prior to pancreatic cancer was associated with increased pancreatic cancer risk (OR=3.48, 95% CI 2.13-5.71). Risk was also elevated for long-term diabetes of 10 years or more (OR=4.73, 95% CI 2.20-10.17). Other medical conditions were not associated with risk. Conclusions: Our results suggest that individuals with long-term diabetes or family history of pancreatic or prostate cancer are at increased risk of pancreatic cancer. Our finding that the association with family history of prostate cancer was present only in never smokers suggests a common etiology between the two tumor types and further investigation is warranted. Citation Format: Gordon Fehringer, Steven Gallinger, Ayelet Borgida, Li Rita Zhang, Geoffrey Liu, Rayjean J. Hung. Family history of cancers, medical history, and pancreatic cancer risk in the Ontario Pancreatic Cancer Case-Control Study. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4810. doi:10.1158/1538-7445.AM2013-4810
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".