The global, regional, and national burden and quality of care index (QCI) of kidney cancer; a Global Burden of Disease systematic analysis 1990–2019
Bibliographic record
Abstract
Abstract Background Kidney cancer is a prevalent cancer worldwide. The incidence and mortality rates of Kidney Cancer (KC) have risen in recent decades. The quality of care provided to KC patients is a concern for public health. Considering the importance of KC, in this study, we aim to assess the burden of the disease, gender and age disparities globally, regionally and nationally to evaluate the quality and inequities of KC care. Methods The 2019 Global Burden of Disease study provides data on the burden of the KC. The secondary indices, including mortality-to-incidence ratio, disability-adjusted life years (DALYs)-to-prevalence ratio, prevalence-to-incidence ratio, and years of life lost (YLLs)-to-years lived with disability (YLDs) ratio, were utilized. These four newly merged indices were converted to the quality-of-care index (QCI) as a summary measure using principal component analysis (PCA). QCI ranged between 0 and 100, and higher amounts of QCI indicate higher quality of care. gender disparity ratio (GDR) was calculated by dividing QCI for females by males to show gender inequity. Results The global age-standardized incidence and mortality rates of KC increased by 29.1% (95% uncertainty interval 18.7 to 40.7) and 11.6% (4.6 to 20.0) between 1990 and 2019, respectively. Globally, the QCI score for KC increased by 14.6% during 30 years, from 71.3 to 81.6. From 1990 to 2019, the QCI score has increased in all Socio-demographic Index (SDI) quintiles. By 2019, the highest QCI score was in regions with a high SDI (93.0), and the lowest was in low SDI quintiles (38.2). Based on the World Health Organization regions, the QCI score was highest in the Region of the Americas, with Canada having the highest score (99.6) and the lowest in the African Region, where the Central African Republic scored the lowest (17.2). In 1990, the GDR was 0.98, and in 2019, it was 0.97 showing an almost similar QCI score for females and males. Conclusion Although the quality of care for kidney cancer has improved from 1990 to 2019, there is a significant gap between nations and different socioeconomic levels. This study provides clinicians and health authorities with a global perspective on the quality of care for KC and identifies the existing disparities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.008 | 0.016 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".