Patients qualified for partial nephrectomy surgery based on radiological diagnosis of
kidney tumor will be prospectively identified. Thirty milliliters of venous blood will be
collected one day prior to the procedure. Blood samples will be sent to the laboratory,
where, in addition to the standard preoperative tests (blood count, creatinine, urea,
fasting glucose), the following parameters will be determined: C-reactive protein,
ferritin, total cholesterol, low density lipoprotein, high density lipoprotein, and
triglycerides. At the time of patient enrollment in the study, a clinical and demographic
interview will be conducted. In addition, the hospital's electronic medical records will
be used to obtain preoperative conventional imaging test results related to tumor
characteristics. During the treatment, perioperative parameters will also be collected,
including the presence of APF defined intraoperatively by the surgeon. APF is defined as
"perinephric fat adherent to the renal parenchyma, making renal dissection difficult"
with the presence defined by the surgeon as 1 - present, 0 - absent. The patient's
participation in the study will not affect the type or technique of the surgery, and
therefore, the risk of complications. After obtaining the histopathological result, data
regarding the removed tumor will be collected. During the observation period (6, 12, 24,
and 60 months after treatment), oncological and functional outcomes will be assessed and
recorded. The observation will be conducted according to the treating physician's
recommendations, in accordance with current medical knowledge, and its modification is
not the subject of this study. Patient data will be collected and stored in an electronic
database. The assessment of the relationship between the various blood parameters,
demographic characteristics (age, gender), clinical characteristics (such as BMI,
presence of metabolic syndrome, tumor size), and the presence of APF will be performed
using univariate analysis (Chi-square, univariate logistic regression) and multivariate
analysis (logistic regression models). When evaluating the impact of APF on perioperative
and oncological outcomes, confounding variables (such as tumor stage, surgical method,
surgeon) will be taken into account when creating predictive models.