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Related Concept Videos

Cancer Survival Analysis01:21

Cancer Survival Analysis

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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...
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Kaplan-Meier Approach01:24

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The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
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Actuarial Approach01:20

Actuarial Approach

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The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
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  9. Predictive And Prognostic Markers
  11. Development And Validation Of A Nomogram To Predict Overall Survival In Patients With Redefined Anaplastic Thyroid Carcinoma Based On The Seer Database.
  1. Home
  3. Research Domains
  5. Biomedical And Clinical Sciences
  7. Oncology And Carcinogenesis
  9. Predictive And Prognostic Markers
  11. Development And Validation Of A Nomogram To Predict Overall Survival In Patients With Redefined Anaplastic Thyroid Carcinoma Based On The Seer Database.

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Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
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Development and validation of a nomogram to predict overall survival in patients with redefined anaplastic thyroid carcinoma based on the SEER database.

Chuyue Zhang1, Bin Li2, Yan Yang3

  • 1Department of General Surgery, the 920th Hospital of Joint Logistics Support Force, PLA, Kunming, Yunnan, People's Republic of China. zhangchuyue0215@163.com.

International Journal of Clinical Oncology
|April 7, 2024

View abstract on PubMed

Summary
This summary is machine-generated.
Keywords:
AnaplasticNomogramPrimary squamous cell carcinoma of thyroidPrognosis

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Primary squamous cell carcinoma of the thyroid (PSCCTh) is now classified as anaplastic thyroid carcinoma (ATC). This study developed a nomogram to predict survival for redefined anaplastic thyroid carcinoma (rATC) and found distinct prognostic factors for ATC and PSCCTh.

Area of Science:

  • Endocrinology
  • Oncology
  • Pathology

Background:

  • The 2022 WHO classification reclassifies primary squamous cell carcinoma of the thyroid (PSCCTh) under anaplastic thyroid carcinoma (ATC).
  • Understanding the distinct characteristics and prognostic factors of these entities is crucial for accurate diagnosis and treatment.

Purpose of the Study:

  • To differentiate between ATC and PSCCTh based on their clinical characteristics.
  • To develop and validate a nomogram for predicting overall survival (OS) in redefined anaplastic thyroid carcinoma (rATC).

Main Methods:

  • Utilized data from the SEER database (2000-2018) for ATC and PSCCTh patients.
  • Employed Kaplan-Meier analysis, log-rank tests, and Cox proportional hazards regression for survival and prognostic factor analysis.
Risk
SEER program
Thyroid carcinoma
  • Constructed and validated nomograms to predict 3-, 6-, and 12-month OS for rATC.

    • Main Results:

    • Included 1338 ATC and 127 PSCCTh patients; PSCCTh showed better OS and cancer-specific survival (CSS) than ATC.
    • Identified distinct independent prognostic factors for CSS: ATC (age, tumor size, metastasis, surgery, radiotherapy, chemotherapy) vs. PSCCTh (age, surgery).
    • Developed a nomogram with good discrimination (C-indexes 0.740 training, 0.778 validation) and calibration for predicting rATC survival.

    Conclusions:

    • A validated nomogram provides a reliable tool for predicting OS in rATC patients.
    • Prognostic factors differ significantly between ATC and PSCCTh, necessitating tailored clinical management strategies.
    • These findings support distinct clinical treatment and management plans for ATC and PSCCTh.