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. 2023 Jun 16;18(1):20230723.
doi: 10.1515/med-2023-0723. eCollection 2023.

Bladder cancer screening: The new selection and prediction model

Vladan Radosavljevic  1 , Natasa Milic  2
Affiliations

Bladder cancer screening: The new selection and prediction model

Vladan Radosavljevic et al. Open Med (Wars). .

Abstract

The objective of this study was to offer new approach for selection of persons with asymptomatic bladder cancer (BC) and highly risky persons for the BC occurrence. Also, it is a part of the BC screening protocol (study is ongoing). Study populations were 100 newly diagnosed (diagnosis maximum 1-year old) males with BC and 100 matched (by sex and age ±5 years) controls (not oncology patients from the same hospital). A hospital based, matched case-control study was done. Statistical analysis comprised of four steps: t-test, univariate logistic regression, multivariate logistic regression, and scoring. The fifth step comprised of two changes, deleting one variable and addition of another variable. Six variables were statistically significant: Caucasian men over 45 years age, tobacco smoking over 40 pack-years, occupational and/or environmental exposure to the proved BC carcinogens over 20 years, macrohematuria, difficulty urinating, BC in relatives up to fourth degree of kinships, and they were used for an easy and fast selection of the individuals with high risk for BC occurrence and BC asymptomatic patients (optimal selection at the population level). The final results showed highly significant probability (p < 0.001), with area under ROC curve of 0.913, negative predictive values of 89.7% (95% CI 10.3-100%), and a specificity of 78%. Positive predictive value was 80.5% (95% CI 19.5-100%) and a sensitivity of 91%. It is possible to recruit asymptomatic BC patients (primary prevention) by using this model, as well as persons with high risk for BC occurrence (primordial prevention). This study is the first part of the BC screening protocol and the second part of the BC screening protocol study is ongoing (urine analysis).

Keywords: bladder cancer; model; prediction; screening; selection.

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Conflict of interest statement

Conflict of interest: Authors state no conflict of interest.

Figures

Figure 1
Figure 1
(Brief self-explanatory legend) Area under ROC curve of 0.913, NPV of 89.7% (95% CI 10.3–100%), and a specificity of 78%. PPV was 80.5% (95% CI 19.5–100%) and a sensitivity of 91%.
See this image and copyright information in PMC

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