American Society of Clinical Oncology Position Statement on Obesity and Cancer
Bibliographic record
Abstract
Over the last 3 decades, the prevalence of obesity in the United States and globally has increased dramatically. More than one third of US adults and 17% of US children and adolescents are categorized as obese. In addition to its well-known risk for heart disease and diabetes, obesity is also a major risk factor for cancer. Increasing evidence has linked obesity to elevated risk of cancer, recurrence, and cancer-related mortality among individuals with early-stage disease. Obese individuals have a worse prognosis after a cancer diagnosis. Obesity can interfere with the delivery of systemic therapy, contribute to morbidity of cancer treatment, and may increase the risk of second malignancies and comorbidities. A cancer diagnosis may serve as a teachable moment to motivate obese individuals to implement a risk-reducing or health-protective lifestyle. Oncology care providers and the oncology team have a close relationship with patients during the critical period after a cancer diagnosis and are in a unique position to help patients lose weight and make other healthy lifestyle changes. The American Society of Clinical Oncology has established a multifaceted initiative to address the burden imparted by obesity on individual cancer patients and society. Major elements of this initiative include the following: (1) increase both provider and patient core knowledge of current evidence on the role of energy balance in cancer risk and prevention; (2) provide guidance, tools, and resources to oncology providers to allow them to use the most appropriate methods based on current knowledge to help cancer patients make needed changes in lifestyle behaviors; (3) build and foster a robust research agenda to study the pathophysiology of energy balance alterations, to investigate whether changes in lifestyle after diagnosis (dietary, weight loss, exercise) will improve prognosis, and to find the best methods to help cancer survivors initiate and maintain lifestyle changes; and (4) advocate and promote policy and systems change that address societal factors contributing to obesity and improve access of cancer patients to weight management services. Obesity is a complex condition and disease and a multifaceted societal problem with many contributing factors. It will take significant time and effort to reduce the incidence of overweight and obesity. Concerted action by oncologists, other health providers, and organizations, as well as patients and their families, is needed to convert growing knowledge of the relationship between obesity and cancer into meaningful action.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.019 | 0.024 |
| Insufficient payload (model declined to judge) | 0.034 | 0.029 |
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".