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Time-to-Surgery and Survival Outcomes in Resectable Colorectal Liver Metastases: A Multi-Institutional Evaluation

2016· article· en· W2267182664 on OpenAlexaff
Julie N. Leal, Alexsander K. Bressan, Neeta Vachharajani, Mithat Gönen, T. Peter Kingham, Michael I. D’Angelica, Peter J. Allen, Ronald P. DeMatteo, Majella B. Doyle, Oliver F. Bathe, Paul D. Greig, Alice C. Wei, William C. Chapman, Elijah Dixon, William R. Jarnagin

Bibliographic record

VenueJournal of the American College of Surgeons · 2016
Typearticle
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsUniversity Health NetworkUniversity of TorontoUniversity of CalgaryPrincess Margaret Cancer CentreFoothills Medical Centre
FundersNational Cancer Institute
KeywordsMedicineHazard ratioProportional hazards modelSurvival analysisUnivariate analysisInternal medicineCohortRetrospective cohort studySurgeryLog-rank testChemotherapyColorectal cancerOncologyMultivariate analysisConfidence intervalCancer

Abstract

fetched live from OpenAlex

BACKGROUND: Resection of colorectal liver metastases (CRLM) is associated with improved survival; however, the impact of time to resection on survival is unknown. The current multi-institutional study sought to evaluate the influence of time from diagnosis (Dx) to resection (Rx) on survival outcomes among patients with resectable, metachronous CRLM and to compare practice patterns across hospitals. STUDY DESIGN: Medical records of patients with ≤4 metachronous CRLM treated with surgery were reviewed and analyzed retrospectively. Time from Dx to Rx was analyzed as a continuous variable and also dichotomized into 2 groups (group 1: Dx to Rx <3 months and group 2: Dx to Rx ≥3 months) for additional analysis. Survival time distributions after resection were estimated using the Kaplan-Meier method. Between-group univariate comparisons were based on the log-rank test and multivariable analysis was done using Cox proportional hazards model. RESULTS: From 2000 to 2010, six hundred and twenty-six patients were identified. Type of initial referral (p < 0.0001) and use of neoadjuvant (p = 0.04) and/or adjuvant (p < 0.0001) chemotherapy were significantly different among hospitals. Patients treated with neoadjuvant chemotherapy (n = 108) and those with unresectable disease at laparotomy (n = 5) were excluded from final evaluation. Median overall survival and recurrence-free survival were 74 months (range 63.8 to 84.2 months) and 29 months (range 23.9 to 34.1 months), respectively. For the entire cohort, longer time from Dx to Rx was independently associated with shorter overall survival (hazard ratio = 1.12; 95% CI, 1.06-1.18; p < 0.0001), but not recurrence-free survival. Median overall survival for group 1 was 76 months (range 62.0 to 89.2 months) vs 58 months (range 34.3 to 81.7 months) in group 2 (p = 0.10). Among patients with available data pertaining to adjuvant chemotherapy (N = 457; 318 treated and 139 untreated), overall survival (87 months [range 71.2 to 102.8 months] vs 48 months [range 25.3 to 70.7 months]; p <0.0001), and recurrence-free survival (33 months [range 25.3 to 40.7 months] vs 22 months [range 14.5 to 29.5 months]; p = 0.05) were improved significantly. CONCLUSIONS: In select patients undergoing initial resection for CRLM, longer time from Dx to Rx is independently associated with worse overall survival. In addition, despite uniform disease characteristics, practice patterns related to definitely resectable CRLM vary significantly across hospitals.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.061
GPT teacher head0.284
Teacher spread0.223 · 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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Citations42
Published2016
Admission routes1
Has abstractyes

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