Evidence map›Paper›PMID 27000271›Full record

ArticleJournal of experimental & clinical cancer research : CR2016

Subpopulation Treatment Effect Pattern Plot (STEPP) analysis of Ki67 assay according to histology: prognostic relevance for resected early stage 'pure' and 'mixed' lobular breast cancer.

Luisa Carbognin, Isabella Sperduti, Matteo Brunelli, Lisa Marcolini, Rolando Nortilli, Sara Pilotto, Ilaria Zampiva, Sara Merler, Elena Fiorio, Elisa Filippi and 6 more

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In one paragraph

Article in Journal of experimental & clinical cancer research : CR, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

16 authors.

Luisa CarbogninMedical Oncology, University of Verona, Azienda Ospedaliera Universitaria Integrata, P.le L.A. Scuro 10, 37124, Verona, Italy.
Isabella SperdutiBiostatistics, Regina Elena National Cancer Institute, Rome, Italy.
Matteo BrunelliDepartment of Pathology and Diagnostic, University of Verona, Azienda Ospedaliera Universitaria Integrata, Verona, Italy.
Lisa MarcoliniDepartment of Pathology and Diagnostic, University of Verona, Azienda Ospedaliera Universitaria Integrata, Verona, Italy.
Rolando NortilliMedical Oncology, University of Verona, Azienda Ospedaliera Universitaria Integrata, P.le L.A. Scuro 10, 37124, Verona, Italy.
Sara PilottoMedical Oncology, University of Verona, Azienda Ospedaliera Universitaria Integrata, P.le L.A. Scuro 10, 37124, Verona, Italy.
Ilaria ZampivaMedical Oncology, University of Verona, Azienda Ospedaliera Universitaria Integrata, P.le L.A. Scuro 10, 37124, Verona, Italy.
Sara MerlerMedical Oncology, University of Verona, Azienda Ospedaliera Universitaria Integrata, P.le L.A. Scuro 10, 37124, Verona, Italy.
Elena FiorioMedical Oncology, University of Verona, Azienda Ospedaliera Universitaria Integrata, P.le L.A. Scuro 10, 37124, Verona, Italy.
Elisa FilippiMedical Oncology, University of Verona, Azienda Ospedaliera Universitaria Integrata, P.le L.A. Scuro 10, 37124, Verona, Italy.
Erminia ManfrinBiostatistics, Regina Elena National Cancer Institute, Rome, Italy.
Francesca PelliniChirurgia 'A', Department of Surgery and Oncology, University of Verona, Azienda Ospedaliera Universitaria Integrata, Verona, Italy.
Franco BonettiBiostatistics, Regina Elena National Cancer Institute, Rome, Italy.
Giovanni Paolo PolliniDepartment of Pathology and Diagnostic, University of Verona, Azienda Ospedaliera Universitaria Integrata, Verona, Italy.
Giampaolo TortoraMedical Oncology, University of Verona, Azienda Ospedaliera Universitaria Integrata, P.le L.A. Scuro 10, 37124, Verona, Italy.
Emilio BriaMedical Oncology, University of Verona, Azienda Ospedaliera Universitaria Integrata, P.le L.A. Scuro 10, 37124, Verona, Italy. emilio.bria@univr.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe aim of this analysis was to investigate the potential impact of Ki67 assay in a series of patients affected by early stage invasive lobular carcinoma (ILC) undergone surgery.

methodsClinical-pathological data were correlated with disease-free and overall survival (DFS/OS). The maximally selected Log-Rank statistics analysis was applied to the Ki67 continuous variable to estimate appropriate cut-offs. The Subpopulation Treatment Effect Pattern Plot (STEPP) analysis was performed to assess the interaction between 'pure' or 'mixed' histology ILC and Ki67.

resultsAt a median follow-up of 67 months, 10-years DFS and OS of 405 patients were 67.8 and 79.8%, respectively. Standardized Log-Rank statistics identified 2 optimal cut-offs (6 and 21%); 10-years DFS and OS were 75.1, 66.5, and 30.2% (p = 0.01) and 84.3, 76.4 and 59% (p = 0.003), for patients with a Ki67 < 6%, between 6 and 21%, and >21%, respectively. Ki67 and lymph-node status were independent predictor for longer DFS and OS at the multivariate analysis, with radiotherapy (for DFS) and age (for OS). Ki67 highly replicated at the internal cross-validation analysis (DFS 85%, OS 100%). The STEPP analysis showed that DFS rate decreases as Ki67 increases and those patients with 'pure' ILC performed worse than 'mixed' histology.

conclusionsDespite the retrospective and exploratory nature of the study, Ki67 was able to significantly discriminate the prognosis of patients with ILC, and the effect was more pronounced for patients with 'pure' ILC.

Indexed as

AdultAgedAged, 80 and overBreast NeoplasmsCarcinoma, LobularFemaleHumansKi-67 AntigenMiddle AgedPrognosisRetrospective StudiesSurvival AnalysisTreatment OutcomeKi-67 AntigenBreast cancerKi67Lobular

Identifiers

PMID27000271
PMCPMC4802900

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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.