Evidence map›Paper›PMID 35070881›Full record

ArticleGland surgery2021

Prognostic value of residual cancer burden and Miller-Payne system after neoadjuvant chemotherapy for breast cancer.

Wei Wang, Yinhua Liu, Hong Zhang, Shuang Zhang, Xuening Duan, Jingming Ye, Ling Xu, Jianxin Zhao, Yuanjia Cheng, Qian Liu

Abstract read
In one paragraph

Article in Gland surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

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21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

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  12. Validation of prognostic and predictive value of total tumoral load after primary systemic therapy in breast cancer using OSNA assay.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2024
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

10 authors.

Wei WangBreast Disease Center, Peking University First Hospital, Beijing, China.
Yinhua LiuBreast Disease Center, Peking University First Hospital, Beijing, China.
Hong ZhangPathology Department, Peking University First Hospital, Beijing, China.
Shuang ZhangPathology Department, Peking University First Hospital, Beijing, China.
Xuening DuanBreast Disease Center, Peking University First Hospital, Beijing, China.
Jingming YeBreast Disease Center, Peking University First Hospital, Beijing, China.
Ling XuBreast Disease Center, Peking University First Hospital, Beijing, China.
Jianxin ZhaoBreast Disease Center, Peking University First Hospital, Beijing, China.
Yuanjia ChengBreast Disease Center, Peking University First Hospital, Beijing, China.
Qian LiuBreast Disease Center, Peking University First Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo verify the feasibility of using the residual cancer burden (RCB) index to stratify prognosis of patients after neoadjuvant chemotherapy (NAC) and to compare RCB with the Miller-Payne system.

methodsWe retrospectively analyzed clinicopathological data of patients receiving treatment between January 1, 2010 and December 31, 2018. Kaplan-Meier curves were used to compare the survival outcomes and estimate disease-free survival (DFS) and disease-specific survival (DSS). Harrell's concordance index (C-index) was used to evaluate the predictive accuracy of RCB and Miller-Payne system.

resultsA total of 423 female patients with complete data were included in the analysis, with a median follow-up time of 58.5 months (range, 7-126 months); 84 patients experienced recurrence, and 48 experienced breast cancer related death. RCB index and the Miller-Payne system were associated with prognosis in the whole cohort. Patients who achieved RCB-I had similar survival outcomes as those with pathological complete response (pCR, RCB-0). In whole cohort, for the RCB index and the Miller-Payne system, respectively, C-indexes for DFS were 0.73 and 0.64, for DSS were 0.74 and 0.64. The average RCB score was different among three subtypes (F=9.335, P<0.001).

conclusionsThe RCB index and the Miller-Payne system can stratify survival outcome of patients after NAC, and RCB had a superior prediction accuracy, especially for triple-negative breast cancer (TNBC). New cut-off value should be sought in order to improve prediction accuracy.

Indexed as

Breast cancerMiller‐Payne systemneoadjuvant chemotherapyprognosisresidual cancer burden

Identifiers

PMID35070881
PMCPMC8749085

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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.