Evidence map›Paper›PMID 31993394›Full record

ArticleIranian journal of public health2019

Landmark Prediction of Survival for Breast Cancer Patients: A Case Study in Tehran, Iran.

Behnaz Alafchi, Leili Tapak, Omid Hamidi, Jalal Poorolajal, Hossein Mahjub

Open access · goldAbstract read
In one paragraph

Article in Iranian journal of public health, 2019. 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

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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

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Behnaz AlafchiDepartment of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
Leili TapakDepartment of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
Omid HamidiDepartment of Science, Hamedan University of Technology, Hamedan, Iran.
Jalal PoorolajalResearch Center for Health Sciences, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
Hossein MahjubDepartment of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
Hamedan University of Medical Sciences · IRHamedan University of Technology · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast cancer is the first non-cutaneous malignancy in women and the second cause of death due to cancer all over the world. There are situations where researchers are interested in dynamic prediction of survival of patients where traditional models might fail to achieve this goal. We aimed to use a dynamic prediction model in analyzing survival of breast cancer patients.

methodsWe used a data set originates from a retrospective cohort (registry-based) study conducted in 2014 in Tehran, Iran, information of 550 patients were available analyzed. A method of landmarking was utilized for dynamic prediction of survival of the patients. The criteria of time-dependent area under the curve and prediction error curve were used to evaluate the performance of the model.

resultsAn index of risk score (prognostic index) was calculated according to the available covariates based on Cox proportional hazards. Therefore, hazard of dying for a high-risk patient with breast cancer within the next five years was 2.69 to 3.04 times of that for a low-risk patient. The value of the dynamic C-index was 0.89 using prognostic index as covariate.

conclusionGenerally, the landmark model showed promising performance in predicting survival or probability of dying for breast cancer patients in this study in a predefined window. Therefore, this model can be used in other studies as a useful model for investigating the survival of breast cancer patients.

Indexed as

Breast neoplasmsCohort studiesDynamic predictionLandmarkingSurvival analysis

Identifiers

PMID31993394
PMCPMC6974853
OpenAlexW2995175841

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