Evidence map›Paper›PMID 39051553›Full record

ArticleCancer reports (Hoboken, N.J.)2024

Nomogram for predicting outcomes in elderly women with mucinous breast cancer: A retrospective study combined with external validation in southwest China.

Zhaoxia Zhang, Chenghao Zhanghuang, Qian Cai, Guangye Song, Quan Wang, Yue Tang, Hongbo Li

Abstract readValidation Study
In one paragraph

Article in Cancer reports (Hoboken, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers 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

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Zhaoxia ZhangDepartment of Urology; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering; Chongqing Key Laboratory of Pediatrics; Ministry of Education Key Laboratory of Child Development and Disorders; National Clinical Research Center for Child Health and Disorders; China International Science and Technology Cooperation base of Child development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, People's Republic of China.ORCID 0009-0007-2226-9560
Chenghao ZhanghuangDepartment of Urology; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering; Chongqing Key Laboratory of Pediatrics; Ministry of Education Key Laboratory of Child Development and Disorders; National Clinical Research Center for Child Health and Disorders; China International Science and Technology Cooperation base of Child development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, People's Republic of China.
Qian CaiDepartment of Cardiothoracic Surgery, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation Base of Child Development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China.
Guangye SongDepartment of Urology, Affiliated Hospital of Yunnan University (The Second People's Hospital of Yunnan Province, Ophthalmic Hospital of Yunnan Province), Kunming, People's Republic of China.
Quan WangDepartment of Surgery, Kunming Hospital of Traditional Chinese Medicine, Kunming, People's Republic of China.
Yue TangDepartment of Surgery, Kunming Hospital of Traditional Chinese Medicine, Kunming, People's Republic of China.
Hongbo LiDepartment of Surgery, Kunming Hospital of Traditional Chinese Medicine, Kunming, People's Republic of China.

Funding

Chongqing Science and Technology Foundation 2023MSXM070Chongqing Science and Technology Foundation NCRCCHD-2021-YP-17
6 · The paper itself

Abstract

objectiveMucinous breast cancer (MBC) is a kind of breast cancer (BC), which is rare in clinic, mainly for women, because of the low incidence rate, so there is no unified standard treatment protocol. Elderly patients have a poor prognosis due to their combined comorbidities. This study aims to investigate the effect of surgery and chemoradiotherapy on the prognosis of elderly female MBC patients and construct nomograms for predicting the OS and CSS in elderly female MBC patients.

methodsData for female MBC patients over 65 years are obtained from the Surveillance, Epidemiology and End Results (SEER) database, patients were divided into two groups: the training set and the validation set. External validation data of the prediction model were provided by Kunming Hospital of Traditional Chinese Medicine. We used Cox regression modeling, which was used to identify independent risk factors affecting patient prognosis. After avoiding confounding bias according to the multifactorial Cox regression model, we used these screened statistically significant results to construct column-line plots. The performance of the model was tested using the consistency index (c-index), the calibration curve, and the area under the operating characteristic curve of the receiver (AUC). Subsequently, we used decision curve analysis (DCA) to examine the potential clinical value of our nomograms.

resultsA total of 8103 elderly MBC female patients were extracted from the database SEER and were assigned to the training and validation set, randomly. A total of 83 patients from Kunming Hospital of Traditional Chinese Medicine were used in the external verification set. After multifactorial Cox regression analysis, we found that age, race, T-stage, M-stage, surgical approach, radiotherapy, and tumor size were independent risk factors for OS in elderly MBC patients. Similarly, independent risk factors of CSS included age, marital status, N stage, M stage, surgical approach, chemotherapy, and tumor size. The C-index for the OS training, validation, and external verification set were 0.731 (95%CI 0.715-0.747), 0.738 (95%CI 0.724-0.752), and 0.809 (95%CI 0.731-0.8874). The C-index of the training set, the validation set, and external verification set for CSS were 0.786 (95%CI 0.747-0.825), 0.776 (95%CI 0.737-0.815), and 0.84 (95%CI0.754-0.926), respectively. The AUC, calibration curves and DCA also showed good accuracy.

conclusionsIn this study, we construct a new nomogram to predict the prognosis of elderly patients with MBC. The nomograms have undergone internal and external validation and have been confirmed to have good clinical applicability. At the same time, we found that for elderly female MBC patients, surgery and radiotherapy significantly benefit their survival, but chemotherapy is not conducive to patient survival.

Indexed as

Adenocarcinoma, MucinousBreast NeoplasmsNomogramsSEER ProgramAgedAged, 80 and overChemoradiotherapyChinaFemaleHumansPrognosisRetrospective StudiesRisk FactorsCSSelderlymucinous breast cancernomogramOSSEER

Identifiers

PMID39051553
PMCPMC11270325

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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.