Risks associated with cancer screening programmes among multimorbid patients: a systematic review
Notice bibliographique
Résumé
Abstract Background Cancer screening programmes have been implemented to facilitate early detection of cancer. However, there are risks associated with cancer screening, such as overdiagnosis. This means identifying problems that were never going to cause harm1. This includes identification of abnormalities that do not progress, or that progress too slowly to cause symptoms or harm during a person’s remaining lifetime in the context of multi-morbidity1,2. Aim We conducted a systematic review of the literature to explore the harms associated with overdiagnosis in multimorbid patients when they undergo three different types of cancer screening programmes. Methods The search was conducted on MEDLINE, EMBASE, PSYCHINFO and Scopus from 1960 (cancer screening programmes implementation) until November 2023. Inclusion criteria involved studies with multimorbid participants (having two or more chronic conditions), having one of three common types of cancers (i.e., breast, prostate and lung), and used a standardised method for screening (i.e., mammography, Prostate-specific antigen test, and Low Dose Computed tomography (LDCT) or Computed Tomography scans (CT)). Only peer-reviewed studies published in English were included. Four keyword sets were used, “Multimorbidity”, “Overdiagnosis “, “Patient harms” and “Cancer screening”. Two independent reviewers conducted the search and data extraction. Rayyan web application was used to help with title, and abstract screening, and to compare the independent reviews. The Newcastle-Ottawa scale was used for quality assessment. This systematic review was registered with PROSPERO database (CRD42024475175) and followed the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guidance. Ethical approval was not required to undertake this review. Results A total of 200 studies resulted from all the databases search and duplicates (n=29) removed. Titles, abstracts and full-texts were screened, with seven studies meeting the inclusion criteria. Quality assessment of the included studies showed two studies of good quality and five studies of poor quality. All included studies were conducted in the United States. Breast cancer overdiagnosis increased with increasing the number of comorbidities. Rates of overdiagnosis with prostate cancer were higher compared to breast cancer, with multimorbid patients having a 15% higher risk of overdiagnosed malignancies, compared to non-multimorbid individuals. Harms of overdiagnosis were categorised into psychological (e.g. anxiety), physical (e.g. side effects of medications) and financial (e.g. costs to healthcare systems). Overdiagnosis with lung cancer was associated with increased anxiety, with more individuals dying from other causes than lung cancer in post-mortem studies, questioning the risk versus benefit of lung cancer screening result interpretation for non-progressive disease. Conclusion The emergence of sophisticated testing technologies and greater access to screening tests can contribute to overdiagnosis. We found many different types of harm related to overdiagnosis in common types of cancer. Further research is required to explore the risk of overdiagnosis with other types of cancer. Awareness of clinicians about the risks of overdiagnosis, particularly in high-risk population, such as multimorbid patients, could guide their decision-making regarding non-progressive cancer treatment. References 1. Neal CH, Helvie MA. Overdiagnosis and risks of breast cancer screening. Radiologic Clinics. 2021 Jan 1;59(1):19-27.. 2. Petrazzuoli F, Morin L, Angioni D, Pecora N, Cherubini A. Polypharmacy, Overdiagnosis and Overtreatment. The Role of Family Physicians in Older People Care. 2022:325-40.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,022 | 0,034 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,004 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».