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The prognostic value of the albumin/neutrophil-to-lymphocyte ratio in colorectal cancer patients: a retrospective cohort study.

코호트 1/5 보강
Frontiers in oncology 2026 Vol.16() p. 1668103
Retraction 확인
출처

PICO 자동 추출 (휴리스틱, conf 3/4)

유사 논문
P · Population 대상 환자/모집단
환자: low ANLR (<15
I · Intervention 중재 / 시술
surgical resection at a single institution between 2015 and 2017
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
[CONCLUSION] ANLR is a promising prognostic biomarker for predicting PFS and OS in CRC patients, with additional value in assessing sarcopenia and complication risks. ANLR-based nomograms provide a valuable tool for personalized survival prediction, supporting tailored treatment strategies to improve patient outcomes.

Xie H, Xu N, Wei L, Tang S, Gan J

📝 환자 설명용 한 줄

[BACKGROUND] The Albumin/Neutrophil-to-Lymphocyte Ratio (ANLR) integrates inflammatory and nutritional pathways, yet its prognostic utility in colorectal cancer (CRC) remains underexplored.

🔬 핵심 임상 통계 (초록에서 자동 추출 — 원문 검증 권장)
  • p-value p < 0.001
  • 95% CI 0.630-0.880
  • OR 0.564
  • HR 0.739
  • 추적기간 65 months
  • 연구 설계 cohort study

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BibTeX ↓ RIS ↓
APA Xie H, Xu N, et al. (2026). The prognostic value of the albumin/neutrophil-to-lymphocyte ratio in colorectal cancer patients: a retrospective cohort study.. Frontiers in oncology, 16, 1668103. https://doi.org/10.3389/fonc.2026.1668103
MLA Xie H, et al.. "The prognostic value of the albumin/neutrophil-to-lymphocyte ratio in colorectal cancer patients: a retrospective cohort study.." Frontiers in oncology, vol. 16, 2026, pp. 1668103.
PMID 41971429

Abstract

[BACKGROUND] The Albumin/Neutrophil-to-Lymphocyte Ratio (ANLR) integrates inflammatory and nutritional pathways, yet its prognostic utility in colorectal cancer (CRC) remains underexplored. This study investigates the association between ANLR and progression-free survival (PFS) as well as overall survival (OS) in CRC patients, aiming to clarify its clinical significance and utility in treatment decision-making.

[METHODS] This retrospective cohort study included 1,436 CRC patients who underwent surgical resection at a single institution between 2015 and 2017. Survival curves for PFS and OS were generated using the Kaplan-Meier method, with differences compared via log-rank tests. Cox proportional hazards regression models were used to evaluate the relationship between ANLR and survival outcomes, while logistic regression analysis assessed the independent association of ANLR with sarcopenia and postoperative complications. Nomograms incorporating ANLR and other significant prognostic factors were constructed to predict 1-, 3-, and 5-year survival rates. The clinical utility of these models was validated using decision curve analysis (DCA) against traditional TNM staging.

[RESULTS] The median follow-up duration was 65 months (interquartile range: 41-78 months). Patients with low ANLR (<15.51) had significantly poorer 5-year PFS (48.2% vs. 63.0%, p < 0.001) and OS (50.9% vs. 65.8%, p < 0.001) compared to those with high ANLR (≥15.51). ANLR demonstrated superior predictive efficacy for outcomes compared to other inflammation-nutrition indices. Multivariate Cox regression identified high ANLR as an independent predictor of improved PFS (hazard ratio [HR] = 0.745, 95% CI: 0.630-0.880, p = 0.001) and OS (HR = 0.739, 95% CI: 0.622-0.878, p = 0.001). Additionally, high ANLR was independently associated with a 40.7% lower risk of sarcopenia (Odds Ratio [OR] = 0.593, 95% CI: 0.442-0.796, p < 0.001) and a reduced risk of complications (OR = 0.564, 95% CI: 0.429-0.742, p < 0.001). The ANLR-based nomograms showed high predictive accuracy (C-indices: 0.719 for PFS, 0.727 for OS) and outperformed TNM staging, confirming greater clinical utility.

[CONCLUSION] ANLR is a promising prognostic biomarker for predicting PFS and OS in CRC patients, with additional value in assessing sarcopenia and complication risks. ANLR-based nomograms provide a valuable tool for personalized survival prediction, supporting tailored treatment strategies to improve patient outcomes.

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