Bibliographic record
Abstract
Estimates indicate that although the number of survivors of childhood cancers is increasing, the majority of those who have survived for 5 years or longer have at least 1 chronic health condition, according to new data.1 Researchers, led by Siobhan Phillips, PhD, MPH, assistant professor of preventive medicine at Northwestern University in Chicago, Illinois, estimated the number of survivors of childhood cancer in the United States to be 388,501, an increase of 59,849 from a 2005 estimate by investigators at the NCI. Among the survivors, approximately 84% survived for 5 or more years after diagnosis. The researchers evaluated cancer incidence and survival data recorded between 1975 and 2011 from 9 Surveillance, Epidemiology, and End Results registries (SEER) in the United States and data from the Childhood Cancer Survivor Study cohort. The studies provided information regarding adverse and late effects of cancer treatment from more than 14,000 longterm survivors of childhood cancers at 26 cancer centers across the United States and Canada. Using the probability of each measure of morbidity from the Childhood Cancer Survivor Study, investigators then multiplied these estimates by the relevant estimate number of US survivors from the SEER data. Dr. Phillips and her colleagues, in collaboration with the NCI and St. Jude Children's Research Hospital, found that an estimated 70% of childhood cancer survivors had a mild or moderate chronic condition, whereas an estimated 32% had a severe, disabling, or life-threatening chronic condition. The findings demonstrate that a singular focus on curing cancer does not offer a complete picture of cancer survivorship, Dr. Phillips says, adding that the burden of these chronic conditions is “profound, both in occurrence and severity.” As a result, she urges the cancer community to focus on how to effectively decrease the morbidity burden and develop care and rehabilitation models that optimize longevity and well-being among survivors of childhood cancer. Dr. Phillips says many of the morbidities are somewhat modifiable in the general population; however, the same prevention guidelines may not apply to survivors of childhood cancers. Among the preventive factors that health care researchers and providers need to better understand are physical activity, diet, and the treatment of characteristics that may make survivors more susceptible to these morbidities, she says.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".