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Record W4224322822 · doi:10.14740/wjon1445

Long-Term Cardiac Disease- and Cancer-Associated Mortalities in Patients With Non-Metastatic Stomach Adenocarcinoma Receiving Resection and Chemotherapy: A Large Competing-Risk Population-Based Cohort Study

2022· article· en· W4224322822 on OpenAlexvenueno aff
Lei Huang, Yan Shi, Ya Jie Zhao, Lei Wang, Wei Hu, Zheng Zhu, Jun Zhang

Bibliographic record

VenueWorld Journal of Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicGastric Cancer Management and Outcomes
Canadian institutionsnot available
FundersNational Cancer InstituteNational Institutes of HealthChinese Medical Association
KeywordsMedicineCohortChemotherapyCardiotoxicityHazard ratioCancerInternal medicinePopulationCohort studyEpidemiologyProportional hazards modelAdenocarcinomaSurgeryOncologyConfidence interval

Abstract

fetched live from OpenAlex

Background: The survival of patients with non-metastatic gastric adenocarcinoma (nmGaC), who are receiving more and more frequently chemotherapy, has improved throughout the last decades, while treatment-caused cardiotoxicity remains a major concern. This study aimed to investigate competing causes of mortality and prognostic factors within a large cohort of patients with resected nmGaC, and to describe the heart-specific mortalities of patients undergoing resection and chemotherapy and of all resected patients. Methods: In this population-based cohort study, data on patients diagnosed with nmGaC from 2004 through 2016, managed with resection with or without chemotherapy, followed up until the end of 2016, and surviving ≥ 1 month were retrieved from the US Surveillance, Epidemiology, and End Results-18 Program. Cumulative mortality functions were calculated. Prognostic factors for heart- and cancer-specific mortalities were evaluated using both multivariable-adjusted Fine-Gray subdistribution and cause-specific hazard functions. Results: Together 21,257 patients with resected nmGaC were eligible for analysis with an accumulated follow-up of 73,711 person-years, where 10,718 (50%) also underwent chemotherapy. Mortalities were overestimated when using the Kaplan-Meier method. Heart diseases were the most common non-cancer cause of mortality. Compared with all resected patients, heart-specific mortality of those also receiving chemotherapy was lower overall and especially at older ages. In the total group of patients, the 8-year cumulative mortalities from heart diseases were 4.4% and 2.0% in resected patients and those also receiving chemotherapy, respectively; in patients ≥ 80 years, the heart disease-specific mortalities were as high as 11.1% and 6.5%, respectively. In overall patients undergoing resection, older ages, black ethnicity, and location at gastric antrum/pylorus were associated with increased heart-specific mortality, while more recent period, female sex, Asian/Pacific Islanders, invasion of serosa, and more positive lymph nodes were associated with lower heart-specific mortality; among those further receiving chemotherapy, only the associations with period of diagnosis, age, and ethnicity were significant. Associations with older ages were stronger for heart-specific mortality than for cancer-associated mortality. Conclusions: Among survivors with resected nmGaC receiving chemotherapy, heart-specific mortality, the most common one among non-cancer causes of mortality, is not higher compared to overall resected patients in this observational study, suggesting that chemotherapy may be relatively safely administered to selected patients under strict indications. Age and ethnicity were major factors associated with heart-specific mortality in both overall resected patients and those further receiving chemotherapy. Overall and stratified cause-specific cumulative incidences of mortality are provided, which can be more clinically useful than the Kaplan-Meier estimates. Our study provides clinically useful evidence for tailored patient management.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.289
Teacher spread0.278 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2022
Admission routes1
Has abstractyes

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