MétaCan
Menu
Back to cohort
Record W4399326644 · doi:10.1007/s12325-024-02893-y

Direct and Indirect Costs of Breast Cancer and Associated Implications: A Systematic Review

2024· review· en· W4399326644 on OpenAlexaboutno aff
Matthew Franklin, Daniel Pollard, Janvi Sah, Annabel Rayner, Yuxiao Sun, France Dube, Anthea Sutton, Lei Qin

Bibliographic record

VenueAdvances in Therapy · 2024
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsnot available
FundersAstraZeneca
KeywordsMedicineBreast cancerEconLitIndirect costsHealth careHealth economicsMEDLINEDisease burdenEpidemiologyEnvironmental healthFamily medicineCancerPublic healthDemographyEconomic growthPopulationPathologyAccountingInternal medicineBusiness

Abstract

fetched live from OpenAlex

INTRODUCTION: Breast cancer is currently the leading cause of global cancer incidence. Breast cancer has negative consequences for society and economies internationally due to the high burden of disease which includes adverse epidemiological and economic implications. Our aim is to systematically review the estimated economic burden of breast cancer in the United States (US), Canada, Australia, and Western Europe (United Kingdom, France, Germany, Spain, Italy, Norway, Sweden, Denmark, Netherlands, and Switzerland), with an objective of discussing the policy and practice implications of our results. METHODS: We included English-language published studies with cost as a focal point using a primary data source to inform resource usage of women with breast cancer. We focussed on studies published since 2017, but with reported costs since 2012. A systematic search conducted on 25 January 2023 identified studies relating to the economic burden of breast cancer in the countries of interest. MEDLINE, Embase, and EconLit databases were searched via Ovid. Study quality was assessed based on three aspects: (1) validity of cost findings; (2) completeness of direct cost findings; and (3) completeness of indirect cost findings. We grouped costs based on country, cancer stage (early compared to metastatic), and four resource categories: healthcare/medical, pharmaceutical drugs, diagnosis, and indirect costs. Costs were standardized to the year 2022 in US (US$2022) and International (Int$2022) dollars. RESULTS: Fifty-three studies were included. Studies in the US (n = 19) and Canada (n = 9) were the majority (53%), followed by Western European countries (42%). Healthcare/medical costs were the focus for the majority (89%), followed by pharmaceutical drugs (25%), then diagnosis (17%) and indirect (17%) costs. Thirty-six (68%) included early-stage cancer costs, 17 (32%) included metastatic cancer costs, with 23% reporting costs across these cancer stages. No identified study explicitly compared costs across countries. Across cost categories, cost ranges tended to be higher in the US than any other country. Metastatic breast cancer was associated with higher costs than earlier-stage cancer. When indirect costs were accounted for, particularly in terms of productivity loss, they tended to be higher than any other estimated direct cost (e.g., diagnosis, drug, and other medical costs). CONCLUSION: There was substantial heterogeneity both within and across countries for the identified studies' designs and estimated costs. Despite this, current empirical literature suggests that costs associated with early initiation of treatment could be offset against potentially avoiding or reducing the overall economic burden of later-stage and more severe breast cancer. Larger scale, national, economic burden studies are needed, to be updated regularly to ensure there is an ongoing and evolving perspective of the economic burden of conditions such as breast cancer to inform policy and practice.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.489
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.000
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 head0.040
GPT teacher head0.334
Teacher spread0.294 · 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

Citations20
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueAdvances in TherapySame topicEconomic and Financial Impacts of CancerFrench-language works237,207