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Record W4318070812 · doi:10.1001/jamaoncol.2022.6911

Association of Inflammatory Biomarkers With Survival Among Patients With Stage III Colon Cancer

2023· article· en· W4318070812 on OpenAlexaff
En Cheng, Qian Shi, Anthony F. Shields, Andrew B. Nixon, Ardaman Shergill, Chao Ma, Katherine A. Guthrie, Félix Couture, Philip Kuebler, Pankaj Kumar, Benjamin Kye Jyn Tan, Smitha Krishnamurthi, Kimmie Ng, Eileen M. O’Reilly, Justin C. Brown, Philip A. Philip, Bette J. Caan, Elizabeth M. Cespedes Feliciano, Jeffrey A. Meyerhardt

Bibliographic record

VenueJAMA Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsHôtel-Dieu de Québec
FundersNational Cancer Institute
KeywordsMedicineInternal medicineHazard ratioColorectal cancerProportional hazards modelCancerOncologyBiomarkerProspective cohort studyCohortConfidence interval

Abstract

fetched live from OpenAlex

Importance: The association of chronic inflammation with colorectal cancer recurrence and death is not well understood, and data from large well-designed prospective cohorts are limited. Objective: To assess the associations of inflammatory biomarkers with survival among patients with stage III colon cancer. Design, Setting, and Participants: This cohort study was derived from a National Cancer Institute-sponsored adjuvant chemotherapy trial Cancer and Leukemia Group B/Southwest Oncology Group 80702 (CALGB/SWOG 80702) conducted between June 22, 2010, and November 20, 2015, with follow-up ending on August 10, 2020. A total of 1494 patients with plasma samples available for inflammatory biomarker assays were included. Data were analyzed from July 29, 2021, to February 27, 2022. Exposures: Plasma inflammatory biomarkers (interleukin 6 [IL-6], soluble tumor necrosis factor α receptor 2 [sTNF-αR2], and high-sensitivity C-reactive protein [hsCRP]; quintiles) that were assayed 3 to 8 weeks after surgery but before chemotherapy randomization. Main Outcomes and Measures: The primary outcome was disease-free survival, defined as time from randomization to colon cancer recurrence or death from any cause. Secondary outcomes were recurrence-free survival and overall survival. Hazard ratios for the associations of inflammatory biomarkers and survival were estimated via Cox proportional hazards regression. Results: Of 1494 patients (median follow-up, 5.9 years [IQR, 4.7-6.1 years]), the median age was 61.3 years (IQR, 54.0-68.8 years), 828 (55.4%) were male, and 327 recurrences, 244 deaths, and 387 events for disease-free survival were observed. Plasma samples were collected at a median of 6.9 weeks (IQR, 5.6-8.1 weeks) after surgery. The median plasma concentration was 3.8 pg/mL (IQR, 2.3-6.2 pg/mL) for IL-6, 2.9 × 103 pg/mL (IQR, 2.3-3.6 × 103 pg/mL) for sTNF-αR2, and 2.6 mg/L (IQR, 1.2-5.6 mg/L) for hsCRP. Compared with patients in the lowest quintile of inflammation, patients in the highest quintile of inflammation had a significantly increased risk of recurrence or death (adjusted hazard ratios for IL-6: 1.52 [95% CI, 1.07-2.14]; P = .01 for trend; for sTNF-αR2: 1.77 [95% CI, 1.23-2.55]; P < .001 for trend; and for hsCRP: 1.65 [95% CI, 1.17-2.34]; P = .006 for trend). Additionally, a significant interaction was not observed between inflammatory biomarkers and celecoxib intervention for disease-free survival. Similar results were observed for recurrence-free survival and overall survival. Conclusions and Relevance: This cohort study found that higher inflammation after diagnosis was significantly associated with worse survival outcomes among patients with stage III colon cancer. This finding warrants further investigation to evaluate whether anti-inflammatory interventions may improve colon cancer outcomes. Trial Registration: ClinicalTrials.gov Identifier: NCT01150045.

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 score0.004
Threshold uncertainty score0.641

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.272
Teacher spread0.262 · 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

Citations43
Published2023
Admission routes1
Has abstractyes

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