Abstract SY28-03: Extending the paradigm of hormonal dependency of cancer to account for effects of lifestyle on risk and prognosis
Bibliographic record
Abstract
Abstract Cancer behavior is determined by cancer metabolism. Abnormalities in cancer cell metabolism are determined in part by intrinsic or autonomous characteristics of each cancer cell, which relate to in part to genetic alterations in oncogenes and cancer suppressor genes, and in part to host effects, which are mediated in large part by hormones and growth factors. Dietary and lifestyle factors that influence cancer risk or cancer prognosis influence levels of hormones such as insulin. We now recognize that these hormones influence the behavior of a subset of common cancers. Attempts to treat cancer by altering the hormonal milieu related to gonadal steroids have led to many widely used treatments for cancer of the breast and prostate, but it remains uncertain if this paradigm can be extended to lifestyle and nutritionally regulated hormones such as insulin, which have been found to be growth-stimulatory in certain preclinical models. We will review these concepts, including recent laboratory and clinical data related to metformin, an anti-diabetic drug under study for possible anti-neoplastic activity. Citation Format: Michael N. Pollak. Extending the paradigm of hormonal dependency of cancer to account for effects of lifestyle on risk and prognosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr SY28-03.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".