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Record W4411627939 · doi:10.1001/jamasurg.2025.1888

A Predictive Tool for Ability to Remain at Home After Cancer Surgery in Older Adults

2025· article· en· W4411627939 on OpenAlexaffabout
Julie Hallet, Alyson Mahar, Wing C. Chan, Daniel I. McIsaac, Natalie G. Coburn, Anna Gombay, Matthew P. Guttman, Barbara Haas, Amy T. Hsu, Frances C. Wright, Lesley Gotlib-Conn, Jessica Armah, Tyler R. Chesney, Douglas G. Manuel, Pietro Galuzzo

Bibliographic record

VenueJAMA Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsBruyèreOttawa HospitalUniversity of OttawaQueen's UniversityHealth Sciences CentreUniversity of TorontoInstitute for Clinical Evaluative SciencesSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineCancerPopulationRetrospective cohort studyResidenceEmergency medicinePhysical therapySurgeryDemographyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Importance: Shared decision-making with older adults regarding cancer surgery is critical. Prognostication tools that report individualized risk estimates of patient-centered outcomes can facilitate discussions. Objective: To develop and internally validate a risk prediction model, STAYHOME, to estimate the risk of losing the ability to live at home for older adults after cancer surgery. Design, Setting, and Participants: This was a retrospective population-based prognostic study conducted in Ontario, Canada. Included were adults 70 years and older undergoing cancer surgery over the period 2007 to 2019. Data were analyzed from June 2023 to January 2024. Exposures: Predictor variables selected among information available preoperatively. The predictive model included age, sex, rural residence, previous cancer diagnosis, type of surgery, frailty, preoperative home care use, neoadjuvant therapy, cancer site, and cancer stage. Main Outcomes and Measures: Inability to stay at home, defined as admission to nursing home. Fine-Gray models accounting for the competing risk of death were used. Discrimination and calibration were assessed. Bootstrap validation using 1000 samples with replacement was performed. Results: Among 97 353 patients (median [IQR] age, 76 [73-81] years; 61 370 female [63.0%]), there were 2658 events (2.7%) at 6 months and 3746 events (3.8%) events at 12 months. The mean predicted risk of not staying home was 2.4% at 6 months and 3.4% at 12 months. Areas under the curve were 0.76 and 0.75 for 6-and 12-month predictions, respectively. Deviation from the observed risk of not staying home was 0.33% (95% CI, 0.31%-0.34%) for 6-month predictions and 0.46% (95% CI, 0.44%-0.48%) for 12-month predictions. Calibration was maintained across risk deciles. Conclusions and Relevance: Results of this prognostic study reveal that STAYHOME used information available preoperatively to predict the risk of not remaining home after cancer surgery for older adults. It presented good discrimination and was well calibrated. Individualized risk estimates from STAYHOME may support counseling, shared decision-making, and setting of expectations before surgery.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.276
Teacher spread0.264 · 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.

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

Citations1
Published2025
Admission routes2
Has abstractyes

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