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Related Concept Videos

Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...

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Related Experiment Video

Updated: Jul 16, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
06:46

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

Prognostic Disparities in Multiple versus Single Primary OSCC: A Large-Cohort Analysis and Predictive Modelling.

Qiang Xu1, Bingju Gao2, Xianglong Zheng2

  • 1Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China; Department of Oral and Maxillofacial Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China; School and Hospital of Stomatology, Fujian Medical University, Fuzhou, China; Department of Oral and Maxillofacial Surgery, School and Hospital of Stomatology, Wenzhou Medical University, Wenzhou, China.

International Dental Journal
|July 14, 2026
PubMed
Summary

Patients with multiple primary oral squamous cell carcinoma (OSCC-MPCs) have distinct characteristics and poorer survival than those with single primary OSCC. New nomograms integrating clinical factors and neutrophil-to-lymphocyte ratio (NLR) aid in personalized treatment and surveillance.

Keywords:
Multiple primary cancersNeutrophil-to-lymphocyte ratioNomogramOral squamous cell carcinomaRisk stratification

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Last Updated: Jul 16, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
06:46

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

Area of Science:

  • Oncology
  • Cancer Research
  • Head and Neck Cancers

Background:

  • Rising incidence of multiple primary cancers in oral squamous cell carcinoma (OSCC) patients poses clinical challenges.
  • Understanding distinct phenotypes and outcomes of OSCC with multiple primary cancers (OSCC-MPCs) versus single primary OSCC (SPOSCC) is crucial.

Purpose of the Study:

  • To characterize clinicopathological phenotypes and survival of OSCC-MPCs compared to SPOSCC.
  • To develop prognostic nomograms for OSCC-MPCs to predict overall survival (OS) and progression-free survival (PFS).

Main Methods:

  • Retrospective cohort study (2015-2025) analyzing clinicopathological data and systemic inflammatory indices.
  • Kaplan-Meier analysis for survival comparison; LASSO regression for predictor identification and nomogram construction.

Main Results:

  • OSCC-MPCs cohort: older, less smoking/alcohol, higher T/lower N stages, elevated preoperative neutrophil-to-lymphocyte ratio (NLR).
  • Significantly inferior 5-year OS (51.28% vs. 79.85%) and PFS (37.97% vs. 63.05%) in OSCC-MPCs vs. SPOSCC.
  • Independent predictors identified: age > 60, advanced T/N, NLR > 2.5, treatment modalities; nomograms showed reliable discrimination.

Conclusions:

  • OSCC-MPCs display unique phenotypes and significantly worse survival than SPOSCC.
  • Developed nomograms integrating clinicopathological features and NLR offer non-invasive tools for tailored therapy and surveillance.