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Record W4417153602 · doi:10.1093/sleep/zsaf389

From sleepless nights to brighter days: tackling insomnia to prevent the development of depression in cancer survivors

2025· article· en· W4417153602 on OpenAlexaff
Josée Savard

Bibliographic record

VenueSLEEP · 2025
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsInsomniaDepression (economics)CancerSleep (system call)Sleep disorderAnxiety

Abstract

fetched live from OpenAlex

Dear Editor, Insomnia is one of the most common psychological problems reported by cancer patients, affecting 30%–60% of them at some point during their treatment trajectory [1]. When left untreated, insomnia, particularly at the syndrome level, persists for months in a substantial proportion of patients [2]. Yet, too often insomnia remains undetected and undertreated. Chronic insomnia takes a heavy toll on the individual and society. Consequences of persistent insomnia include increased symptoms that are already frequent in cancer patients, such as psychological distress, fatigue, and cognitive disturbances. While the evidence remains inconclusive regarding whether insomnia increases cancer-related mortality [3], our work showed that it is associated with a higher risk of febrile neutropenia and infections during chemotherapy, as well as with treatment dose reductions [4, 5], underscoring the clinical significance of insomnia. Large-scale epidemiological studies conducted in non-cancer individuals have consistently found insomnia to be a risk factor for the subsequent development of other psychological disorders such as depressive, anxiety, and substance-use disorders [6]. The most recent study by Irwin and collaborators [7] published in the current issue of Sleep, supports the role of insomnia as a risk factor for depression in the context of cancer specifically. In their compelling and rigorous population-based prospective cohort study, Irwin et al. [7] followed for over 32 months 636 non-depressed women aged between 55 and 85 years, among whom 315 were early-stage (stages 0–II) breast cancer survivors on average, 6 years post-diagnosis and 321 aged-matched women with no history of breast cancer. Patients were stratified on the presence or absence of insomnia at baseline. The incidence or recurrence of a major depressive disorder (DSM-5 diagnosis) was the main dependent variable. Importantly, the study controlled for many possible confounders including vasomotor symptoms. Results showed that the risk of depression was nearly six times higher in breast cancer survivors as compared to women with no history of breast cancer. Insomnia was associated with a further increase in depression risk in breast cancer survivors, but not in the comparison group. Breast cancer survivors with insomnia had an over nine-fold higher risk of depression than the comparison group. Overall, the study findings suggest that insomnia is a significant risk factor for depression in breast cancer survivors. Obviously, as in any study, this investigation is not without limitations. In addition to those acknowledged by the authors (i.e. possible selection bias limiting the results’ generalizability, insomnia ascertained by a self-report scale rather than an interview), another limitation is related to insomnia being assessed on one occasion only. Insomnia typically has a fluctuating course [8]. Future research should take repeated measures of insomnia and consider its persistence, since chronic insomnia is more likely to have a deleterious impact on patients’ mood than occasional or transient sleep difficulties. However, the fact that a history of DSM-5 insomnia disorder was also predictive of subsequent depression further reinforces this finding. Furthermore, causality cannot be established with certainty between insomnia and the occurrence of depression from an observational study like this. Irwin et al. [7] found that antecedents of depression were also predictive of the development of depression. Hence, it could simply be that persons with a history of depression were more likely to develop depression after their cancer diagnosis. Indeed, a personal history of depression is a well-established risk factor of cancer-related depression [9]. Insomnia would only then be an epiphenomenon. Reverse causality is also possible with antecedents of depression leading to insomnia. Clinical trials are particularly likely to shed light on the causal link between insomnia and depression. A handful of studies conducted in non-cancer populations have shown that offering cognitive-behavioral therapy for insomnia (CBT-I) was associated with a decreased risk of incident depression [10]. The previous trial by Irwin et al. [11] in older adults convincingly supports the role of CBT-I in preventing the onset of depression. These studies add weight to the idea that insomnia has a causal role in the development of depression. While the preventive effect of CBT-I remains to be demonstrated in the cancer context, there is enough strong evidence supporting the systematic screening for insomnia and the integration of CBT-I in routine cancer care. With regard to screening, Irwin et al. [7] suggest using the Insomnia Severity Index (ISI) [12]. The ISI is a psychometrically sound questionnaire that is widely used in research. Although it is relatively brief (seven items), it is unlikely that a multi-item questionnaire could be administered in routine care to detect every potential cancer-related symptom that patients might experience. In a previous study, we found that an effective alternative was to add a single sleep item to the Edmonton Symptom Assessment System-Revised [13], which is already implemented in many cancer centers in North America to systematically screen psychological distress. In terms of treatment, CBT-I is the recommended first-line treatment for chronic insomnia and its efficacy has been demonstrated in a wealth of clinical trials conducted in cancer patients [14, 15]. However, accessibility to this treatment remains a challenge in spite of the increasing evidence supporting the efficacy of low-intensity interventions (e.g. web-based [16–19]) and stepped care CBT-I which integrates a self-help intervention as the first step [20]. Preliminary findings of our current implementation study are encouraging and suggest that it is feasible to implement a stepped care CBT-I in routine cancer care (Savard et al., in preparation). Scalable alternatives suggested by Irwin et al. [7] include Tai Chi and mindfulness-based stress reduction (MBSR) but their efficacy is not as firmly established to treat cancer-related insomnia and one of them (MBSR) was found to be inferior to CBT-I in producing short-term insomnia improvements [21]. From a public health perspective, it is crucial to better communicate to the public and decision-makers about the benefits of treating insomnia early on, in order to reduce the burden and societal costs associated with depression which include increased health care costs and productivity loss. The message needs to be put out there that CBT-I is a fairly straightforward and low-cost intervention that can prevent the development of other psychological disorders that are more complex and costly to treat such as depressive disorders. When offered face-to-face, CBT-I is typically composed of 4–8 sessions, which is considerably shorter than treating a major depressive episode with CBT or any other type of psychotherapy. Low-intensity interventions such as web-based CBT-I cost even less with a somewhat equivalent efficacy. Insomnia is a prevalent and often overlooked issue among cancer survivors, with growing evidence pointing to its role in the development of depression. The study by Irwin et al. adds compelling support to the argument that insomnia is a significant risk factor for psychological disorders in this population. While further research is needed to clarify causality, the current evidence justifies the immediate inclusion of systematic insomnia screening and access to CBT-I in routine cancer care. Addressing insomnia proactively may not only improve sleep but also serve as a preventive measure against the appearance of more severe psychological disorders. Financial disclosure: None. Non-financial disclosure: None.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.312
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2025
Admission routes1
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