Evidence map›Paper›PMID 40566738›Full record

Observational studyCancer investigation2025

Chemotherapy and Persistent Depression in Older Mexican Cancer Survivors: Secondary Analysis of the Mexican Health and Aging Study.

Diego Arriaga-Izabal, Francisco Morales-Lazcano, Adrián Canizalez-Román

Abstract readObservational Study
In one paragraph

Observational study in Cancer investigation, 2025. 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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0cells of the map it votes in
0citing papers in PubMed
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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

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

3 authors.

Diego Arriaga-IzabalAutonomous University of Sinaloa, Culiacan, México.ORCID 0000-0002-0929-6384
Francisco Morales-LazcanoAutonomous University of Sinaloa, Culiacan, México.ORCID 0009-0005-7939-2186
Adrián Canizalez-RománAutonomous University of Sinaloa, Culiacan, México.ORCID 0000-0001-8605-0639

Funding

The Mexican Health and Aging Study - IIR01AG018016 · NIA · UNIVERSITY OF TEXAS MED BR GALVESTON · PI Rebeca Wong · 1999 to 2026
$22.6M
NIA NIH HHS R01 AG018016
6 · The paper itself

Abstract

introductionDepressive symptoms (DS) are prevalent among cancer survivors and may be exacerbated by chemotherapy. However, longitudinal data on this relationship within the Mexican population are lacking. The current study aimed to analyze the relationship between chemotherapy and the persistence of depressive symptoms over time in cancer survivors.

methodsRetrospective observational study using Mexican Study of Health and Aging (MHAS) data (2012-2021). Participants aged 50+ included chemotherapy patients (n = 30) and healthy controls (n = 6,970). Depressive symptoms were assessed with a modified Center for Epidemiologic Studies Depression Scale. Mann-Whitney U, X

resultsChemotherapy recipients showed significantly higher depressive symptoms at early follow-ups (2012, 2015, 2018; p < 0.05), with no significant difference by 2021. Adjusted analyses indicated chemotherapy was associated with a more than twofold increase in odds of depression (OR = 2.165; 95% CI: 1.220-3.810). Lower education and comorbidities such as diabetes and hypertension were also independently linked to increased depression risk.

conclusionsChemotherapy is a significant predictor of persistent depressive symptoms among Mexican cancer survivors aged 50 and above. These findings highlight the critical need for integrated mental health screening and targeted psychosocial care within oncology settings.

Indexed as

Antineoplastic AgentsCancer SurvivorsDepressionNeoplasmsAgedAged, 80 and overFemaleHumansMaleMexicoMiddle AgedRetrospective StudiesRisk FactorsAntineoplastic AgentsCancer survivorsChemotherapyDepressionQuality of life

Identifiers

PMID40566738
PMCPMC13205477

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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.