The Risk of Cancer Might be Lower Than We Think. Alternatives to Lifetime Risk Estimates
Bibliographic record
Abstract
BACKGROUND: Estimates of lifetime cancer risk are commonly used in the clinical setting and in health-care evaluations. These measures are based on lifetime cancer risk estimates and may create an unrealistically frightening perception of cancer risk for an individual. We suggest using two new measures of cancer risk to complement the cancer lifetime risk measure, namely estimates of cancer risk from birth to a specific age or from a specific age to life expectancy. METHODS: We calculated risks using incidence density data from the Israel National Cancer Registry of 2013, applying a well-known formula for calculating risk, for a follow-up time. The joint disease-free survival probability is calculated for several age intervals, and hence the risk (i.e. 1-survival) for the intervals. RESULTS: The risk of cancer to age 80 in Jewish men and women, respectively, ranged from about 0.336 and 0.329 at age 0, to 0.279 and 0.237 at age 60. The risk of cancer from birth up to an age in Jewish men and women, respectively, ranged from 0 and 0 at birth to 0.088 and 0.129 at age 60. The risk of cancer to age 80 in Arab men and women, respectively, ranged from 0.298 and 0.235 at age 0 to 0.249 and 0.161 at age 60. The risk of cancer from birth up to an age in Arab men and women, respectively, ranged from 0 and 0 at age 0 to 0.074 and 0.095 at age 60. In Jewish and Arab women, breast cancer risk to age 80 decreased from about 0.127 in Jewish women at age 40 to 0.079 at age 60 and from 0.080 to 0.043 in Arab women; the risk from birth up to a specific age ranged between 0 and 0.056, and 0 and 0.040, respectively. CONCLUSION: The two proposed new estimates convey important additional information to patients and physicians. These estimates are considerably lower than the frequently quoted 33% lifetime cancer risk and are more relevant to patients and physicians. Similarly, breast cancer risk estimates up to or from a specific age differ considerably from the frequently quoted lifetime risk estimates of 1 in 8 women.
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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 | 0.029 | 0.143 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".