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Abstract IA24: The lifetime impact of cancer and cancer therapy

2020· article· en· W3046179605 on OpenAlexaboutno aff
Greg Armstrong

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCancerQuality of life (healthcare)PopulationDiseasePediatricsMalignancyGerontologyIntensive care medicineEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Abstract Survival rates after childhood cancer have increased dramatically in the past 50 years. More than 80% of children diagnosed with a malignancy now survive five years, with most going on to become long-term survivors. This has resulted in a growing population of childhood cancer survivors in the U.S., estimated to exceed 420,000 in 2013 and to approach half a million by 2020. Unfortunately, the same curative treatments that enable long-term survival also cause toxicities that leave many survivors with a substantial burden of adverse health and quality-of-life outcomes. Survivors have a 13-fold higher mortality rate than the general population. Eighty percent of childhood cancer survivors develop at least one severe, disabling, life-threatening, or fatal chronic health condition by age 45 years, and the average survivor will experience four such conditions by age 50 years. Specifically, survivors have increased risk compared to the general population for diseases often associated with aging, such as heart disease, diminished pulmonary function, and second cancers. The substantial burden of morbidity experienced by survivors translates to a significantly reduced quality of life compared to those without a cancer history. Thus, there is a critical need to better understand which survivors have the highest risk of serious morbidity and mortality, identify those with subclinical dysfunction, and inform intervention strategies for mitigating the burden of these late effects. Unfortunately, however, as survivors age into adulthood, most are no longer followed at their primary treatment institution, but by their community primary care providers, limiting our knowledge of long-term follow and late outcomes, a similar problem to that seen when survivors of adult malignancies participate in clinical trials where systematic follow-up ends at the five-year time point. To address this knowledge gap, the Childhood Cancer Survivor Study (CCSS) was developed. The CCSS is a multi-institutional, multidisciplinary, NCI-funded collaborative resource (U24 CA55727; PI: Gregory Armstrong) established to evaluate long-term outcomes among survivors of childhood cancer, largely by self-reported outcomes. It is a retrospective cohort consisting of >25,000 five-year survivors of childhood cancer who were diagnosed between 1970-1999 at one of 31 participating centers in the U.S. and Canada. Self-reported outcomes across a spectrum of chronic health conditions, psychosocial and cognitive function, and physical function outcomes have informed over 350 publications to date enumerating risk for this aging population. The results of the CCSS have advanced knowledge of late effects among survivors of childhood cancer. CCSS investigators have demonstrated that 60-90% of adults treated for cancer during childhood develop one or more chronic health conditions. They have also shown that by age 50 years, the cumulative incidence of self-reported severe, disabling, life-threatening, or fatal health condition was 53.6% among survivors compared with 19.8% among sibling control group. Among childhood cancer survivors who reach age 35 years of age without a previous severe, disabling, life-threatening, or fatal health condition, 25.9% will experience a new severe, disabling, life-threatening or fatal condition within 10 years as compared to 6% of healthy siblings. In addition to the findings related to an increased risk of morbidity and mortality from subsequent neoplasms and cardiac disease, CCSS has shown that long-term survivors are at risk of developing a variety of adverse outcomes that include organ dysfunction (e.g., pulmonary, gonadal), impaired growth and development, impaired cognitive function, difficulties obtaining employment and insurance, and compromises in the quality of life. Recently, the CCSS provided evidence that survivors treated in more recent eras have a significant reduction in late mortality attributable to two things: fewer deaths from recurrence or progression of primary cancer but more importantly, fewer deaths from treatment-related causes such as subsequent malignancies and cardiopulmonary death. In conclusion, the now decades-long strategy of designing pediatric cancer treatment regimens with a focus on adult health and avoidance of late effects appears to have been successful. Taken along with promotion of early detection of late effects and improved treatment of late effects, this approach has now translated to extend the lifespan of many survivors of childhood cancer. Future directions include the need to: (1) assess the true impact of screening and early detection of late effects on morbidity and mortality and evaluate interventions that improve screening rates as well as alter health behaviors, (2) expand individual risk prediction for poor outcomes, (3) further understand genetic susceptibility for late effects, and (4) target studies for both primary and secondary prevention of late effects, so that we not only extend the lifespan of survivors, but their health span as well. Citation Format: Greg Armstrong. The lifetime impact of cancer and cancer therapy [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr IA24.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.038
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.004
Science and technology studies0.0020.001
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0380.008

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.

Opus teacher head0.169
GPT teacher head0.500
Teacher spread0.332 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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