Evidence map›Paper›PMID 33452761›Full record

ArticleCancer medicine2021

Validity of the prognostication tool PREDICT version 2.2 in Japanese breast cancer patients.

Karen Zaguirre, Masaya Kai, Makoto Kubo, Mai Yamada, Kanako Kurata, Hitomi Kawaji, Kazuhisa Kaneshiro, Yurina Harada, Saori Hayashi, Akiko Shimazaki and 7 more

Abstract readValidation Study
In one paragraph

Article in Cancer medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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

9 citing papers in PubMed.

  1. Article
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  9. Validation of the online PREDICT tool in a cohort of early breast cancer in Brazil.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2022
    Article
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

17 authors.

Karen ZaguirreDepartment of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.ORCID 0000-0003-2380-2762
Masaya KaiDepartment of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Makoto KuboDepartment of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Mai YamadaDepartment of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Kanako KurataDepartment of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Hitomi KawajiDepartment of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.ORCID 0000-0002-8259-8063
Kazuhisa KaneshiroDepartment of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Yurina HaradaDepartment of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Saori HayashiDepartment of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Akiko ShimazakiDepartment of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Takafumi MorisakiDepartment of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Hitomi MoriDepartment of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Yoshinao OdaDepartment of Anatomic Pathology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Sanmei ChenDepartment of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Taiki MoriyamaDepartment of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Shuji ShimizuInternational Medical Department, Kyushu University Hospital, Fukuoka, Japan.
Masafumi NakamuraDepartment of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPREDICT is a prognostication tool that calculates the potential benefit of various postsurgical treatments on the overall survival (OS) of patients with nonmetastatic invasive breast cancer. Once patient, tumor, and treatment details have been entered, the tool will show the estimated 5-, 10-, and 15-year OS outcomes, both with and without adjuvant therapies. This study aimed to conduct an external validation of the prognostication tool PREDICT version 2.2 by evaluating its predictive accuracy of the 5- and 10-year OS outcomes among female patients with nonmetastatic invasive breast cancer in Japan.

methodsAll female patients diagnosed from 2001 to 2013 with unilateral, nonmetastatic, invasive breast cancer and had undergone surgical treatment at Kyushu University Hospital, Fukuoka, Japan, were selected. Observed and predicted 5- and 10-year OS rates were analyzed for the validation population and the subgroups. Calibration and discriminatory accuracy were assessed using Chi-squared goodness-of-fit test and area under the receiver operating characteristic curve (AUC).

resultsA total of 636 eligible cases were selected from 1, 213 records. Predicted and observed OS differed by 0.9% (p = 0.322) for 5-year OS, and 2.4% (p = 0.086) for 10-year OS. Discriminatory accuracy results for 5-year (AUC = 0.707) and 10-year (AUC = 0.707) OS were fairly well.

conclusionPREDICT tool accurately estimated the 5- and 10-year OS in the overall Japanese study population. However, caution should be used for interpretation of the 5-year OS outcomes in patients that are ≥65 years old, and also for the 10-year OS outcomes in patients that are ≥65 years old, those with histologic grade 3 and Luminal A tumors, and in those considering ETx or no systemic treatment.

Indexed as

AdultAgedAge FactorsAntineoplastic AgentsArea Under CurveChi-Square DistributionErb-b2 Receptor Tyrosine KinasesFemaleHumansImmunohistochemistryJapanKaplan-Meier EstimateKi-67 AntigenMiddle AgedPostoperative CarePrognosisAntineoplastic AgentsERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesKi-67 Antigenbreast cancerprognosissurvivalwomen's cancer

Identifiers

PMID33452761
PMCPMC7940221

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Registered trials

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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.