Evidence map›Paper›PMID 37046725›Full record

ArticleCancers2023

A Comparison between the Online Prognostic Tool PREDICT and myBeST for Women with Breast Cancer in Malaysia.

Mohd Nasrullah Nik Ab Kadir, Suhaily Mohd Hairon, Imi Sairi Ab Hadi, Siti Norbayah Yusof, Siti Maryam Muhamat, Najib Majdi Yaacob

Abstract read
In one paragraph

Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

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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

1 citing paper in PubMed.

  1. Review
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

6 authors.

Mohd Nasrullah Nik Ab KadirDepartment of Community Medicine, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia.ORCID 0000-0001-7920-9912
Suhaily Mohd HaironDepartment of Community Medicine, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia.ORCID 0000-0002-4934-0001
Imi Sairi Ab HadiBreast and Endocrine Surgery Unit, Department of Surgery, Hospital Raja Perempuan Zainab II, Ministry of Health Malaysia, Kota Bharu 15586, Kelantan, Malaysia.
Siti Norbayah YusofMalaysian National Cancer Registry Department, National Cancer Institute, Ministry of Health Malaysia, Putrajaya 62250, Federal Territory of Putrajaya, Malaysia.
Siti Maryam MuhamatMalaysian National Cancer Registry Department, National Cancer Institute, Ministry of Health Malaysia, Putrajaya 62250, Federal Territory of Putrajaya, Malaysia.
Najib Majdi YaacobBiostatistics and Research Methodology Unit, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia.ORCID 0000-0002-6860-1430

Funding

Universiti Sains Malaysia USM/PPSP/PG/2.0/012 (21)
6 · The paper itself

Abstract

The PREDICT breast cancer is a well-known online calculator to estimate survival probability. We developed a new prognostic model, myBeST, due to the PREDICT tool's limitations when applied to our patients. This study aims to compare the performance of the two models for women with breast cancer in Malaysia. A total of 532 stage I to III patient records who underwent surgical treatment were analysed. They were diagnosed between 2012 and 2016 in seven centres. We obtained baseline predictors and survival outcomes by reviewing patients' medical records. We compare PREDICT and myBeST tools' discriminant performance using receiver-operating characteristic (ROC) analysis. The five-year observed survival was 80.3% (95% CI: 77.0, 83.7). For this cohort, the median five-year survival probabilities estimated by PREDICT and myBeST were 85.8% and 82.6%, respectively. The area under the ROC curve for five-year survival by myBeST was 0.78 (95% CI: 0.73, 0.82) and for PREDICT was 0.75 (95% CI: 0.70, 0.80). Both tools show good performance, with myBeST marginally outperforms PREDICT discriminant performance. Thus, the new prognostic model is perhaps more suitable for women with breast cancer in Malaysia.

Indexed as

breast neoplasmMalaysiaonline prognostic toolprognosiswomen

Identifiers

PMID37046725
PMCPMC10093426

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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.