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S1701 Mapping the Global Impact: Liver Cancer Attributable to Drug Use Across 204 Countries, 1990-2021: A Benchmarking Analysis

2024· article· en· W4403721777 on OpenAlexaboutno aff
Amit Banerjee, Jobby John, Pragathi Munnangi, Lalitkumar Patel, Venkata Ramana Katikala, Siri Vummaneni, Himanshu Bharatkumar Koyani, George Mathew Mukalil, Bhargav Koyani, Simranpreet Singh Daid, Hardik Dineshbhai Desai, Tanvi Koduru

Bibliographic record

VenueThe American Journal of Gastroenterology · 2024
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBenchmarkingDrugLiver cancerCancerEnvironmental healthInternal medicinePharmacology

Abstract

fetched live from OpenAlex

Introduction: Liver cancer (LC) is the seventh leading cause of death amongst all cancer related causalities, with incidence rates influenced by various risk factors including viral hepatitis and lifestyle choices. Emerging evidence identifies drug use, especially injectable drugs, as a significant risk factor due to its role in the transmission of hepatitis B and C, leading precursors to hepatocellular carcinoma. Despite the known links, research specifically quantifying the burden of LC attributable to Drug use remains limited. Methods: This is the first ever study identifying deaths, years lived with disability (YLDs), years of life lost (YLLs) due to LC attributable to drug use by age, sex, year and location across the 204 Countries and territories from 1990-2021 using global burden of disease 2021 tool. Results: The total number of deaths rose from 17,090 (95% uncertainty interval: 12,161-23,510) in 1990 to 65,499 (50,430-83,777) in 2021. Regionally, Southern Latin America experienced the largest increase in age-standardized death rate (ASMR), surging by 532%, followed by Australasia at 452%, and Southern Sub-Saharan Africa at 245% between 1990 and 2021. Nationally, Canada saw the greatest annual percentage change (APC) in ASMR, increasing by 14.3%, with Greenland next at 8.65% over the same period. In terms of the Socio-Demographic Index (SDI), the highest ASMR was recorded in high SDI countries at 1.14 (0.92-1.38) cases per 100,000 person years in 2021, followed by YLDs at 0.37 (0.25-0.53) and YLLs at 27.58 (22.84-33.34) per 100,000. By age, those under 20 years old showed the highest total percentage change (TPC) in unadjusted death rate at 207%, followed by those aged 55 and older at 98%, and those aged 20-54 at 33% from 1990 to 2021. In terms of gender, TPC in total deaths was 258% for males versus 348% for females, YLDs were 295% for males versus 385% for females, and YLLs were 191% for males versus 276% for females between 1990 and 2021 (Figure 1). Conclusion: Deaths due to LC attributable to drug use accounted for 13.53% of all LC related deaths in 2021 highlights a critical and preventable public health challenge. This emphasizes the urgent need for comprehensive drug prevention and treatment programs, alongside routine screenings within healthcare settings. By addressing drug use robustly, we can significantly reduce the burden of liver cancer and improve public health outcomes.Figure 1.: A: Global trend of liver cancer attributable to drug use in 204 countries and territories from 1990-2021. B: Age-wise burden of liver cancer attributable to drug use in 204 countries and territories in year 1990 and year 2021. C: GBD region wise burden of liver cancer attributable to drug use, age-standardized rate (per 100,000).

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.047
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0070.015
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.021
GPT teacher head0.321
Teacher spread0.299 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes1
Has abstractyes

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