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Record W3091769391 · doi:10.1001/jamasurg.2020.3754

Patient-Centered Time-at-Home Outcomes in Older Adults After Surgical Cancer Treatment

2020· article· en· W3091769391 on OpenAlexafffundabout
Tyler R. Chesney, Barbara Haas, Natalie G. Coburn, Alyson Mahar, Victoria Zuk, Haoyu Zhao, Frances C. Wright, Amy T. Hsu, Julie Hallet

Bibliographic record

VenueJAMA Surgery · 2020
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsBruyèreOttawa HospitalUniversity of ManitobaSunnybrook HospitalHealth Sciences CentreInstitute for Clinical Evaluative SciencesSunnybrook Health Science CentreUniversity of Toronto
FundersCanadian Institutes of Health ResearchIpsenIpsen BiopharmaceuticalsOntario Ministry of Health and Long-Term CareOntario Institute for Cancer Research
KeywordsMedicineCancerMEDLINEGeneral surgeryIntensive care medicineGerontologyInternal medicine

Abstract

fetched live from OpenAlex

Importance: Functional outcomes are central to cancer care decision-making by older adults. Objective: To assess the long-term functional outcomes of older adults after a resection for cancer using time at home as the measure. Design, Setting, and Participants: This population-based cohort study was conducted in Ontario, Canada, using the administrative databases stored at ICES (formerly the Institute for Clinical Evaluative Sciences). The analysis included adults 70 years or older with a new diagnosis of cancer between January 1, 2007, and December 31, 2017, who underwent a resection 90 days to 180 days after the diagnosis. Patients were followed up until and censored at the date of death, date of last contact, or December 31, 2018. Main Outcomes and Measures: The main outcome was time at home, dichotomized as high time at home (defined as ≤14 institution days annually) and low time at home (defined as >14 institution days) during the 5 years after surgical cancer treatment. Time-to-event analyses with Kaplan-Meier methods and multivariable Cox proportional hazards regression models were used. Results: A total of 82 037 patients were included, with a median (interquartile range) follow-up of 46 (23-80) months. Of these patients, 52 119 were women (63.5%) and the mean (SD) age was 77.5 (5.7) years. The median (interquartile range) number of days at home per days alive per patient was high, at 0.98 (0.94-0.99) in postoperative year 1, 0.99 (0.97-1.00) in year 2, 0.99 (0.96-1.00) in year 3, 0.99 (0.96-1.00) in year 4, and 0.99 (0.96-1.00) in year 5. The probability of high time at home was 70.3% (95% CI, 70.0%-70.6%) at postoperative year 1 and 53.2% (95% CI, 52.8%-53.5%) at postoperative year 5. Advancing age (≥85 years: hazard ratio [HR], 2.11; 95% CI, 2.04-2.18); preoperative frailty (HR, 1.74; 95% CI, 1.68-1.80); high material deprivation (5th quintile: HR, 1.25; 95% CI, 1.20-1.29); rural residency (HR, 1.14; 95% CI, 1.10-1.18); high-intensity surgical procedure (HR, 2.04; 95% CI, 1.84-2.25); and gastrointestinal (HR, 1.23; 95% CI, 1.18-1.27), gynecologic (HR, 1.31; 95% CI, 1.18-1.45), and oropharyngeal (HR, 1.05; 95% CI, 0.95-1.16) cancers were associated with low time at home. Inpatient acute care was responsible for 76.0% and long-term care was responsible for 2.0% of institution days in postoperative year 1. Inpatient days decreased to 31.0% by year 3, but days in long-term care increased over time. Conclusions and Relevance: This study found that older adults predominantly experienced high time at home after resection for cancer, reflecting the overall favorable functional outcomes in this population. The oldest adults and those with preoperative frailty and material deprivation appeared to be the most vulnerable to low time at home, and efforts to optimize and manage expectations about surgical outcomes can be targeted for this population; this information is important for patient counseling regarding surgical cancer treatment and for preparation for postoperative recovery.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.029
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.019
GPT teacher head0.260
Teacher spread0.241 · 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 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".

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Citations65
Published2020
Admission routes3
Has abstractyes

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