Evidence map›Paper›PMID 40874217›Full record

ArticleClinical epidemiology2025

Using Restricted Mean Time Lost to Evaluate the Prognostic Effects on Locally Advanced Breast Cancer Considering Competing Risks.

Zhaojin Li, Di Liu, Yawen Hou, Zheng Chen

Abstract read
In one paragraph

Article in Clinical epidemiology, 2025. 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Zhaojin LiDepartment of Biostatistics, School of Public Health (Guangdong Provincial Key Laboratory of Tropical Disease Research), Southern Medical University, Guangzhou, People's Republic of China.
Di LiuDepartment of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, People's Republic of China.
Yawen HouDepartment of Statistics and Data Science, School of Economics, Jinan University, Guangzhou, People's Republic of China.
Zheng ChenDepartment of Biostatistics, School of Public Health (Guangdong Provincial Key Laboratory of Tropical Disease Research), Southern Medical University, Guangzhou, People's Republic of China.ORCID 0000-0003-3201-2666

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In the presence of competing risks, when the baseline risk is unclear, if only the sub-distribution hazard ratio (SHR) is reported in the results, which is related to the cumulative incidence function, the survival disparity of events of interest between groups cannot be clarified. In contrast, the difference in restricted mean time lost (RMTLd), which is the difference in the areas under the cumulative incidence between two groups, can well compensate for the deficiencies of SHR and explain the effects on a time scale, facilitating clinical interpretation and communication. Methods: The Surveillance, Epidemiology, and End Results (SEER) database was used to collect information on female patients with locally advanced breast cancer diagnosed between 2010 and 2015. The prognostic factors of breast cancer death were evaluated considering competing risk. Univariable and multivariable analyses were conducted to get SHR and RMTLd. Results: SHR can indicate the direction of prognostic factors, while RMTLd can quantify prognostic effects and provide time-scale interpretation. For instance, in adjuvant radiotherapy, the SHR showed a protective effect, which can be quantified as an average increase of 4.15 months in survival time. Discussion: In the presence of competing risks, the combined use of absolute measure RMTLd can more intuitively explain the prognostic effect, which is convenient for clinical practice and communication.

Indexed as

competing riskslocally advanced breast cancerrestricted mean time lostsub-distribution hazard ratio

Identifiers

PMID40874217
PMCPMC12380099

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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.