MétaCan
Menu
Back to cohort
Record W4382775277 · doi:10.3389/fonc.2023.1152209

Global estimates of rehabilitation needs and disease burden in tracheal, bronchus, and lung cancer from 1990 to 2019 and projections to 2045 based on the global burden of disease study 2019

2023· article· en· W4382775277 on OpenAlexaff
Xigui Lai, Conghui Li, Yao Yang, Mingyuan Niu, Yujie Yang, Shanshan Gu, Weiqian Hou, Lili Chen, Yi Zhu

Bibliographic record

VenueFrontiers in Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of ChinaInstitute for Health Metrics and EvaluationBill and Melinda Gates Foundation
KeywordsMedicineRehabilitationLung cancerDisease burdenCancerDiseaseBurden of diseaseGlobal healthDemographyPhysical therapyPublic healthInternal medicinePathology

Abstract

fetched live from OpenAlex

Background: The global cancer burden is substantial and spiraling. Although rehabilitation specialists could offer assistance, oncologic rehabilitation is still underutilized and not a routine part of clinical oncology guidelines worldwide. Global investigations of disease prevalence and years lived with disability (YLDs) for tracheal, bronchus, and lung (TBL) cancer are valuable for facilitating clinical practice improvement and health resource management. The objective of this study is to report the global estimates of rehabilitation needs and disease burden of TBL cancers from 1990 to 2019 and provide predictions for 2045. Methods: To estimate the need for rehabilitation, the data used from the Global Burden of Disease Study 2019 to calculate the prevalence, YLDs, and the attributable risk factors of TBL cancer. The Bayesian age-period-cohort model and Auto-Regressive Integrated Moving Average model were established to forecast the future health burden. All analyses were done at the global level and then some in the aggregation with the seven World Bank regions. All the data were analyzed by R software (x64 version 4.2.1) and Microsoft Excel (version 2019). Results: Globally in 2019, 3,212,307 cases of TBL cancer (95% UI 2,937,037-3,488,346) could have benefitted from rehabilitation, contributing to 544,215 (95% UI 396,134-700,099) YLDs. Over the past 30 years, the age-standardized rate (ASR) of prevalence (EAPC = 0.51) and YLDs (EAPC = 0.03) increased. Throughout this period, the global prevalence and YLDs counts were greater in males than females. The ASR of prevalence and YLDs are projected to show a slight downward trend by 2045 on the global scale, the overall prevalence and YLDs due to TBL cancer are likely to increase further, but all indicators show a growing trend in females. Conclusion: TBL cancer remains one of the major public health issues globally. According to the forecasted results, the burden of YLDs due to TBL cancer will continue to rise, and the increment is higher in females than males. A rising number of patients worldwide will benefit from rehabilitation services in the future to achieve precise control and management throughout the TBL cancer patient lifecycle.

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)0.000
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 score0.028
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.011
GPT teacher head0.329
Teacher spread0.318 · 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.

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".

Quick stats

Citations5
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in OncologySame topicCancer survivorship and careFrench-language works237,207