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Record W4404190777 · doi:10.1093/ijpp/riae058.029

Risks associated with cancer screening programmes among multimorbid patients: a systematic review

2024· review· en· W4404190777 on OpenAlexaboutno aff
Nehal Hassan, Colin Newell, Sajida Chaudry, Sally Wilson, Robert Slight, Sarah P. Slight

Bibliographic record

VenueInternational Journal of Pharmacy Practice · 2024
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCancerFamily medicineIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.034
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.511
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.034
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.561
GPT teacher head0.593
Teacher spread0.031 · 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 teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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