Evidence map›Paper›PMID 39595121›Full record

ArticleBiomedicines2024

The Demographic and Clinical Characteristics, Prognostic Factors, and Survival Outcomes of Head and Neck Carcinosarcoma: A SEER Database Analysis.

Wanting Hou, Ouying Yan, Hong Zhu

Abstract read
In one paragraph

Article in Biomedicines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Wanting HouDivision of Abdominal Tumor Multimodality Treatment, Cancer Center, West China Hospital, Sichuan University, Chengdu 610065, China.
Ouying YanDivision of Abdominal Tumor Multimodality Treatment, Cancer Center, West China Hospital, Sichuan University, Chengdu 610065, China.
Hong ZhuDivision of Abdominal Tumor Multimodality Treatment, Cancer Center, West China Hospital, Sichuan University, Chengdu 610065, China.ORCID 0000-0002-2087-3306

Funding

Science and Technology Department of Sichuan Province 2023NSFSC1833
6 · The paper itself

Abstract

backgroundHead and neck carcinosarcoma (HNCS) is a rare and highly aggressive malignancy with limited research, resulting in an incomplete understanding of disease progression and a lack of reliable prognostic tools. This study aimed to retrospectively analyze the clinical characteristics and outcomes of HNCS patients using data from the Surveillance, Epidemiology, and End Results (SEER) database and to develop a nomogram to predict overall survival (OS) and cancer-specific survival (CSS).

methodsPatients diagnosed with HNCS from 1975 to 2020 were identified in the SEER database. Univariate and multivariate Cox regression analyses were conducted to identify independent prognostic indicators, with the optimal model selected using the minimal Akaike Information Criterion (AIC). The identified prognostic factors were incorporated into nomograms to predict OS and CSS. Model performance was assessed using the concordance index (C-index), area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Survival curves were generated using Kaplan-Meier analysis and compared via the log-rank test.

resultsA total of 152 HNCS patients were included, with 108 assigned to the training cohort and 44 to the validation cohort in a 7:3 ratio. Prognostic factors including age, primary tumor site, marital status, radiotherapy, chemotherapy, tumor size, pathological grade, and tumor stage were incorporated into the nomogram models. The models demonstrated strong predictive performance, with C-index values for OS and CSS of 0.757 and 0.779 in the training group, and 0.777 and 0.776 in the validation group, respectively. AUC values for predicting 3-, 5-, and 10-year OS were 0.662, 0.713, and 0.761, and for CSS the values were 0.726, 0.703, and 0.693. Kaplan-Meier analysis indicated significantly improved survival for patients with lower risk scores. The 3-, 5-, and 10-year OS rates for the entire cohort were 54.1%, 45.6%, and 35.1%, respectively, and the CSS rates were 62.9%, 57.5%, and 52.2%, respectively.

conclusionsThis study provides validated nomograms for predicting OS and CSS in HNCS patients, offering a reliable tool to support clinical decision-making for this challenging malignancy. These nomograms enhance the ability to predict patient prognosis and personalize treatment strategies.

Indexed as

cancer-specific survival (CSS)end results database (SEER database)epidemiologyhead and neck carcinosarcoma (HNCS)overall survival (OS)prognostic nomogramsurveillance

Identifiers

PMID39595121
PMCPMC11591622

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.