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Record W4322213218 · doi:10.14740/wjon1560

Nephrolithiasis-Associated Renal Cell Carcinoma in Patients Who Underwent Nephrectomy: A Single-Center Experience

2023· article· en· W4322213218 on OpenAlexvenueno aff
Syah Mirsya Warli, Ben Julian Mantiri, Bungaran Sihombing, Ginanda Putra Siregar, Fauriski Febrian Prapiska

Bibliographic record

VenueWorld Journal of Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicKidney Stones and Urolithiasis Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNephrectomyDiabetes mellitusRenal cell carcinomaBody mass indexKidney diseaseKidney stonesInternal medicineKidney cancerOdds ratioPopulationIncidence (geometry)CancerRisk factorUnivariate analysisMedical recordKidneySurgeryMultivariate analysisEndocrinology

Abstract

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Background: Kidney stones (nephrolithiasis) affect around 5% of the world's population. Some medical disorders, like obesity or diabetes, have increased the incidence and prevalence of nephrolithiasis. In addition, chronic inflammation and infection are frequently linked to kidney stone formation. Urothelial cell proliferation may change as a result of chronic inflammation, tumors will therefore develop as a result of this. The correlation between nephrolithiasis and renal cell cancer can also be explained by shared risk factors. At Adam Malik General Hospital, we strive to identify the risk factor for stone-induced renal cell cancer. Methods: This study was carried out at Adam Malik General Hospital by collecting medical record reports from patients who had nephrectomy for nephrolithiasis between July 2014 and August 2020. A variety of information was obtained, including identification, smoking status, body mass index (BMI), hypertension, diabetes mellitus, and nephrolithiasis history. The histopathological examination of cancer patients was used to determine adjusted odds ratios (ORs) both separately and in combination with other variables. Age, smoking status, BMI, hypertension, and diabetes mellitus all influenced the OR. The single variable was examined using Chi-square test, and the multivariate analysis was carried out using linear regression. Results: A total of 84 patients who underwent nephrectomy due to nephrolithiasis were included in the study, with an average age of 48.77 ± 7.23 years old; 48 (60%) of those were aged < 55 years old. In this study, 52 male patients (63.4%) and 16 patients (20%) were found to have renal cell carcinoma. Univariate analysis showed that the OR of patients with familial history of cancer was 4.5 (95% confidence interval (CI) 2.17 - 19.8), and the OR for smokers was 1.54 (95% CI 1.42 - 1.68). Similar results were shown in patients with hypertension and urinary tract infections due to stones. Nephrolithiasis patients with hypertension were 2.56 (95% CI 1.075 - 6.106) times more likely to develop a malignancy, while patients who had an infection due to a urinary tract stone were 2.85 (95% CI 1.37 - 5.92) times more likely to develop renal cell carcinoma compared to its counterpart. Both have a P-value of less than 0.05. Contrarily, alcoholism and frequent nonsteroidal anti-inflammatory drugs (NSAIDs) user results were different. Both have a P-value of 0.264 and 0.07, respectively. Furthermore, diabetes mellitus type 2 and BMI over 25 are not statistically significant, with a P-value of 0.341 and 0.12, respectively. In multivariable-adjusted analyses, participants with a family history of cancer and recurrent urinary tract infection due to urinary tract stones had a statistically significant increase in overall renal cell carcinoma risk (hazard ratio (HR): 1.39, 95% CI 1.05 - 1.84 and HR: 1.12, 95% CI 1.05 - 1.34). Conclusion: Kidney stone and renal cell carcinoma are significantly correlated due to recurrent urinary tract infection and familial history of cancer, which increases renal cell carcinoma risk.

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 score0.060
Threshold uncertainty score0.724

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.030
GPT teacher head0.297
Teacher spread0.267 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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