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MODEL OF ORGANIZATION OF KIDNEY CANCER EARLY DIAGNOSIS

https://doi.org/10.21294/1814-4861-2021-20-2-68-76

Abstract

 Challenges of early kidney cancer detection and screening significantly increase morbidity and mortality rates, thus dictating the need to improve prevention, early diagnosis and organization of medical care for the population of primorsky Krai.

The aim of the study was to create a model for improving early diagnosis of kidney cancer in the primorsky Krai using the program for assessing the risk of kidney cancer (ARKC). The model included a population questionnaire to identify risk factors and algorithm of patient routing («roadmap») with suspected kidney cancer for in-depth examination and treatment.

Material and Methods. 2982 residents of the primorsky Krai (women – 1950, men – 1032) in the age range 29–75 took part in the questionnaire survey using the ARKC program.

Results. No risk factors were identified in 1879 (63.0 %) individuals. All patients at high risk for kidney cancer (656 – 22.0 %) and patients of the uncertainty group (447 – 15.0 %) were referred for physical and ultrasound examination to exclude kidney tumors. Non-tumor pathology of the kidneys was revealed in 156 (14.0 %) patients. Renal mass suspicious for renal cell carcinoma was revealed in 21 (1.9 %) patients (later confirmed in 17 patients with stage I–II cancer, in 3 patients with stage III, in 1 patient with stage IV). According to the results of the factor analysis, two main groups of factors had a predominant effect on the rise in the overall kidney cancer incidencer. The first group of factors (65.0 %) is caused by smoking, excessive alcohol consumption, overweight, unbalanced nutrition, and the influence of carcinogens. The second group of factors (35.0 %) is caused by problems of a medical and social nature: the low material and technical base of primary care medical organizations, the insufficient professional training of medical workers on the issues of cancer prevention and treatment, including kidney cancer.

Conclusion. To improve the early detection of kidney cancer, a prognostic model with computer program for assessing the individual risk of developing kidney cancer was developed. population survey using the ARKC computer program allowed us to narrow the diagnostic search, form risk groups and effectively route patients with suspected kidney cancer for in-depth examination in accordance with the «road map». 

About the Authors

V. G. Moreva
Far Eastern Federal University, School of Biomedicine
Russian Federation

 MD, PhD, Senior Lecturer, Department of Public Health and Preventive Medicine 

 8, Sukhanov Street, 690950, Vladivostok, Russia 



G. N. Alekseeva
Pacific State Medical University, Institute of Surgery
Russian Federation

 MD, DSc, Associate Professor; Head of Urological Center, Vladivostok Clinical Hospital № 2 

 2, Ostryakov ave., 690002, Vladivostok, Russia 



P. F. Kiku
Far Eastern Federal University, School of Biomedicine
Russian Federation

 MD, DSc, Professor, Head of the Department of Public Health and Preventive Medicine 

 8, Sukhanov Street, 690950, Vladivostok, Russia 



L. I. Gurina
Far Eastern Federal University, School of Biomedicine; Pacific State Medical University, Institute of Surgery
Russian Federation

 MD, DSc, Professor, Department of Clinical Medicine;, Associate Professor of the Institute of Surgery 

 8, Sukhanov Street, 690950, Vladivostok, Russia 

 2, Ostryakov ave., 690002, Vladivostok, Russia 



K. M. Sabirova
Far Eastern Federal University, School of Biomedicine
Russian Federation

 Postgraduate, Department of Public Health and Preventive Medicine

Researcher ID (WOS): U-8505-2018 

 8, Sukhanov Street, 690950, Vladivostok, Russia 



V. N. Rasskazova
Far Eastern Federal University, School of Biomedicine
Russian Federation

 MD, PhD, Senior Lecturer, Department of Public Health and Preventive Medicine 

 8, Sukhanov Street, 690950, Vladivostok, Russia 



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Review

For citations:


Moreva V.G., Alekseeva G.N., Kiku P.F., Gurina L.I., Sabirova K.M., Rasskazova V.N. MODEL OF ORGANIZATION OF KIDNEY CANCER EARLY DIAGNOSIS. Siberian journal of oncology. 2021;20(2):68-76. (In Russ.) https://doi.org/10.21294/1814-4861-2021-20-2-68-76

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ISSN 1814-4861 (Print)
ISSN 2312-3168 (Online)