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Record W4402840988 · doi:10.1016/s2589-7500(24)00152-3

Impact of the COVID-19 pandemic on health-care use among patients with cancer in England, UK: a comprehensive phase-by-phase time-series analysis across attendance types for 38 cancers

2024· article· en· W4402840988 on OpenAlex
Yen Yi Tan, Wai Hoong Chang, Michail Katsoulis, Spiros Denaxas, Kayla C. King, Murray P. Cox, Charles Davie, François Balloux, Alvina G. Lai

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Lancet Digital Health · 2024
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsUniversity of British Columbia
FundersNIHR Great Ormond Street Hospital Biomedical Research CentreWellcome TrustAcademy of Medical SciencesUniversity College London Hospitals Biomedical Research CentreUCLH Biomedical Research CentreMedical Research CouncilNational Institute for Health and Care ResearchUniversity College London
KeywordsAttendancePandemicCoronavirus disease 2019 (COVID-19)Phase (matter)Series (stratigraphy)CancerMedicineNew englandFamily medicinePolitical scienceInternal medicineDiseaseBiology

Abstract

fetched live from OpenAlex

BACKGROUND: The COVID-19 pandemic resulted in the widespread disruption of cancer health provision services across the entirety of the cancer care pathway in the UK, from screening to treatment. The potential long-term health implications, including increased mortality for individuals who missed diagnoses or appointments, are concerning. However, the precise impact of lockdown policies on national cancer health service provision across diagnostic groups is understudied. We aimed to systematically evaluate changes in patterns of attendance for groups of individuals diagnosed with cancer, including the changes in attendance volume and consultation rates, stratified by both time-based exposures and by patient-based exposures and to better understand the impact of such changes on cancer-specific mortality. METHODS: In this retrospective, cross-sectional, phase-by-phase time-series analysis, by using primary care records linked to hospitals and the death registry from Jan 1, 1998, to June 17, 2021, we conducted descriptive analyses to quantify attendance changes for groups stratified by patient-based exposures (Index of Multiple Deprivation, ethnicity, age, comorbidity count, practice region, diagnosis time, and cancer subtype) across different phases of the COVID-19 pandemic in England, UK. In this study, we defined the phases of the COVID-19 pandemic as: pre-pandemic period (Jan 1, 2018, to March 22, 2020), lockdown 1 (March 23 to June 21, 2020), minimal restrictions (June 22 to Sept 20, 2020), lockdown 2 (Sept 21, 2020, to Jan 3, 2021), lockdown 3 (Jan 4 to March 21, 2021), and lockdown restrictions lifted (March 22 to March 31, 2021). In the analyses we examined changes in both attendance volume and consultation rate. We further compared changes in attendance trends to cancer-specific mortality trends. Finally, we conducted an interrupted time-series analysis with the lockdown on March 23, 2020, as the intervention point using an autoregressive integrated moving average model. FINDINGS: From 561 611 eligible individuals, 7 964 685 attendances were recorded. During the first lockdown, the median attendance volume decreased (-35·30% [IQR -36·10 to -34·25]) compared with the preceding pre-pandemic period, followed by a median change of 4·38% (2·66 to 5·15) during minimal restrictions. More drastic reductions in attendance volume were seen in the second (-48·71% [-49·54 to -48·26]) and third (-71·62% [-72·23 to -70·97]) lockdowns. These reductions were followed by a 4·48% (3·45 to 7·10) increase in attendance when lockdown restrictions were lifted. The median consultation rate change during the first lockdown was 31·32% (25·10 to 33·60), followed by a median change of -0·25% (-1·38 to 1·68) during minimal restrictions. The median consultation rate decreased in the second (-33·89% [-34·64 to -33·18]) and third (-4·98% [-5·71 to -4·00]) lockdowns, followed by a 416·16% increase (409·77 to 429·77) upon lifting of lockdown restrictions. Notably, across many weeks, a year-over-year decrease in weekly attendances corresponded with a year-over-year increase in cancer-specific mortality. Overall, the pandemic period revealed a statistically significant reduction in attendances for patients with cancer (lockdown 1 -24 070·19 attendances, p<0·0001; minimal restrictions -19 194·89 attendances, p<0·0001; lockdown 2 -31 311·28 attendances, p<0·0001; lockdown 3 -43 843·38 attendances, p<0·0001; and lockdown restrictions lifted -56 260·50 attendances, p<0·0001) compared with before the pandemic. INTERPRETATION: The UK's COVID-19 pandemic lockdown affected cancer health service access negatively. Many groups of individuals with cancer had declines in attendance volume and consultation rate across the phases of the pandemic. A decrease in attendances might lead to delays in cancer diagnoses, treatment, and follow-up, putting such groups of individuals at higher risk of negative health outcomes, such as cancer-specific mortality. We discuss the factors potentially responsible for explaining changes in service provision trends and provide insight to help inform clinical follow-up for groups of individuals at risk, alongside potential future policy changes in the care of such patients. FUNDING: Wellcome Trust, National Institute for Health Research University College London Hospitals Biomedical Research Centre, National Institute for Health Research Great Ormond Street Hospital Biomedical Research Centre, Academy of Medical Sciences, and the University College London Overseas Research Scholarship.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.076
GPT teacher head0.457
Teacher spread0.381 · 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