Evidence map›Paper›PMID 30598501›Full record

ArticleThe oncologist2019

Depressive Symptom Profiles and Survival in Older Patients with Cancer: Latent Class Analysis of the ELCAPA Cohort Study.

Clément Gouraud, Elena Paillaud, Claudia Martinez-Tapia, Lauriane Segaux, Nicoleta Reinald, Marie Laurent, Lola Corsin, Nicolas Hoertel, Mathilde Gisselbrecht, Elise Mercadier and 7 more

Abstract read
In one paragraph

Article in The oncologist, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. [Risk prediction of demoralization syndrome in patients with oral cancer].Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology · 2025
    Article
  4. Article
  5. Article
  6. Symptom Classes in Decompensated Liver Disease.Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association · 2022
    Article
  7. Review
  8. 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.

Clément GouraudClinical Epidemiology and Ageing Unit, Université Paris-Est, Créteil, France clement.gouraud0@gmail.com.ORCID 0000-0002-0433-023X
Elena PaillaudClinical Epidemiology and Ageing Unit, Université Paris-Est, Créteil, France.
Claudia Martinez-TapiaClinical Epidemiology and Ageing Unit, Université Paris-Est, Créteil, France.
Lauriane SegauxClinical Epidemiology and Ageing Unit, Université Paris-Est, Créteil, France.
Nicoleta ReinaldClinical Epidemiology and Ageing Unit, Université Paris-Est, Créteil, France.
Marie LaurentClinical Epidemiology and Ageing Unit, Université Paris-Est, Créteil, France.
Lola CorsinGeriatric Department, Henri-Mondor Hospital, AP-HP, Créteil, France.
Nicolas HoertelFaculty of Medicine, Paris Descartes University, Sorbonne Paris Cité, Paris, France.
Mathilde GisselbrechtFaculty of Medicine, Paris Descartes University, Sorbonne Paris Cité, Paris, France.
Elise MercadierFaculty of Medicine, Paris Descartes University, Sorbonne Paris Cité, Paris, France.
Pascaline Boudou-RouquetteMedical Oncology Department, Cochin Hospital, AP-HP, Paris, France.
Anne ChahwakilianDepartment of Gerontology, Geriatric Oncology Unit, Broca Hospital, AP-HP, Paris, France.
Sylvie Bastuji-GarinClinical Epidemiology and Ageing Unit, Université Paris-Est, Créteil, France.
Frédéric LimosinFaculty of Medicine, Paris Descartes University, Sorbonne Paris Cité, Paris, France.
Cédric LemogneFaculty of Medicine, Paris Descartes University, Sorbonne Paris Cité, Paris, France.
Florence Canouï-PoitrineClinical Epidemiology and Ageing Unit, Université Paris-Est, Créteil, France.
ELCAPA Study Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe expression of depressive symptoms in older people with cancer is heterogeneous because of specific features of age or cancer comorbidity. We aimed to identify depressive symptom profiles in this population and describe the associated features including survival. MATERIALS AND

methodsPatients ≥70 years who were referred to geriatric oncology clinics were prospectively included in the ELCAPA study. In this subanalysis, depressive symptoms were used as indicators in a latent class analysis. Multinomial multivariable logistic regression and Cox models examined the association of each class with baseline characteristics and mortality.

resultsFor the 847 complete-case patients included (median age, 79 years; interquartile range, 76-84; women, 47.9%), we identified five depressive symptom classes: "no depression/somatic only" (38.8%), "no depression/pauci-symptomatic" (26.4%), "severe depression" (20%), "mild depression" (11.8%), and "demoralization" (3%). Compared with the no depression/pauci-symptomatic class, the no depression/somatic only and severe depression classes were characterized by more frequent comorbidities with poorer functional status and higher levels of inflammation. "Severe" and "mild" depression classes also featured poorer nutritional status, more medications, and more frequent falls. Severe depression was associated with poor social support, inpatient status, and increased risk of mortality at 1 year (adjusted hazard ratio, 1.62, 95% confidence interval, 1.06-2.48) and 3 years (adjusted hazard ratio, 1.49; 95% confidence interval, 1.06-2.10).

conclusionA data-driven approach based on depressive symptoms identified five different depressive symptom profiles, including demoralization, in older patients with cancer. Severe depression was independently and substantially associated with poor survival. IMPLICATIONS FOR PRACTICE: Older patients with cancer present with distinct profiles of depressive symptomatology, including different severity levels of depression and the demoralization syndrome. Clinicians should use a systematic assessment of depressive symptoms to adequately highlight these distinct profiles. Geriatric and oncological features are differently associated with these profiles. For instance, severe depression was associated with more frequent comorbidities with poorer functional, poor nutritional status, polypharmacy, frequent falls, inpatient status and poor social support. Also, severe depression was independently and substantially associated with poor survival so that the identification and management of depression should be considered a high priority in this population.

Indexed as

Latent Class AnalysisAgedAged, 80 and overCohort StudiesDepressionFemaleHumansMaleNeoplasmsSurvival AnalysisCancerClusterDepressionEpidemiologyOld agePsycho‐oncology

Identifiers

PMID30598501
PMCPMC6656460

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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.