Evidence map›Paper›PMID 40777954›Full record

ArticleAfrican health sciences2024

Prognostic impact of diagnostic and therapeutic time delays in breast cancer: an exploratory data analysis for patients at Parirenyatwa Hospital, Zimbabwe.

Bester Saruchera, Oliver Bodhlyera, Henry Mwambi, Ntokozo Ndlovu

Abstract read
In one paragraph

Article in African health sciences, 2024. 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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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.

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.

Bester SarucheraSchool of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, South Africa.
Oliver BodhlyeraSchool of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, South Africa.
Henry MwambiSchool of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, South Africa.
Ntokozo NdlovuDepartment of Oncology, Faculty of Medicine and Health Sciences, University of Zimbabwe, P.O.Box MP167. Mt Pleasant, Harare.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This paper seeks to investigate factors related to time delays for diagnosis and treatment in breast cancer patients at Parirenyatwa Hospital in Zimbabwe and subsequently evaluate the effects of presentation and diagnosis delays on cancer stage. Methods: The study was done for 379 patients with histologically diagnosed invasive breast cancer, from 2015 through to 2019. The study sought to identify factors associated with the time delays ( months)using parametric and non-parametric methods, depending on whether underlying assumptions of such tests are met. A multiple logistic regression model was also used to analyse the association between factors, primary delay, secondary delay variables and cancer stage. Results: The median of the primary, secondary and treatment delay were found to be 7.6, 1 and 0.4 months respectively. Rural residence, Karnofsky Performance Score below 70%, hypertension comorbidity, tumor size (>5cm) and well differentiated tumors (grade 1) were significant factors for delayed presentation. Longer primary delay times and post-menopausal status were associated with secondary delay. Advanced cancer stage at diagnosis and those on medical aid were more likely to have a delay in treatment onset. Conclusion: Primary and secondary delay were predictive of advanced disease using logistic regression.

Indexed as

Breast NeoplasmsDelayed DiagnosisTime-to-TreatmentAdultAgedFemaleHumansLogistic ModelsMiddle AgedNeoplasm StagingPrognosisTime FactorsZimbabweBreast cancerprimary delaysecondary delaytreatment delayZimbabwe

Identifiers

PMID40777954
PMCPMC12327112

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