Early-stage cancer may develop without specific clinical manifestations, which makes timely diagnosis difficult. Conventional diagnostic methods, including imaging and histopathological examination, remain fundamental, but minimally invasive laboratory markers can provide additional information during the diagnostic process. Serum biomarkers such as PSA, CEA, CA 19-9, CA 125, and AFP are associated with particular clinical applications, although their diagnostic performance varies considerably. Individual biomarkers may have insufficient sensitivity or specificity for reliable early cancer detection. Combining several markers can potentially improve diagnostic discrimination by reflecting different biological characteristics of malignant disease. At the same time, false-positive results may occur because of benign diseases, inflammation, organ dysfunction, or physiological conditions. Evaluation of biomarker panels within an integrated clinical algorithm is therefore relevant for improving diagnostic accuracy and risk assessment.
To evaluate the diagnostic and prognostic significance of serum tumor biomarker panels in patients with suspected early-stage cancer and to determine their potential contribution to clinical risk stratification.
The study framework includes patients undergoing diagnostic evaluation for suspected malignant disease. Clinical history, presenting symptoms, physical examination findings, laboratory parameters, imaging results, and final pathological diagnoses are assessed. Venous blood samples are collected before definitive treatment, and selected serum tumor biomarkers are determined using standardized laboratory assays. Depending on the suspected tumor localization, appropriate combinations of biomarkers are analyzed. Diagnostic performance is assessed using sensitivity, specificity, positive predictive value, negative predictive value, and receiver operating characteristic analysis. Biomarker results are compared with imaging and histopathological findings. Clinical risk stratification incorporates tumor stage, biological characteristics, patient-related factors, and the pattern of biomarker elevation. Particular attention is given to false-positive and false-negative findings.
Assessment of multiple serum biomarkers provides broader diagnostic information than isolated marker evaluation in selected clinical situations. Different biomarkers may demonstrate complementary diagnostic characteristics, allowing a combined profile to provide additional information for identifying patients at increased probability of malignant disease. However, the diagnostic value of a panel depends on the type and stage of cancer, the selected biomarkers, assay methodology, and cutoff values. Some biomarkers may show increased sensitivity but limited specificity, while others demonstrate greater specificity with lower sensitivity in early disease. Combining markers can partially compensate for these limitations when the selected biomarkers reflect different tumor-associated processes. Biomarker results also provide supplementary information for clinical risk stratification and may be useful for monitoring changes during treatment or follow-up. Nevertheless, elevated serum biomarker levels should not be interpreted as definitive evidence of malignancy without appropriate clinical, imaging, and pathological confirmation.
Serum tumor biomarker panels can serve as useful complementary instruments for early-stage cancer assessment and clinical risk stratification. Their minimally invasive nature allows repeated testing and integration into longitudinal patient monitoring. The combined assessment of selected biomarkers may provide greater diagnostic information than a single marker, particularly when interpreted alongside clinical and imaging findings. However, serum biomarkers alone are insufficient to establish a definitive cancer diagnosis. Their effective clinical application requires standardized laboratory methods, validated cutoff values, appropriate patient selection, and correlation with histopathological findings. Further development of multimarker models combining serum biomarkers with molecular and imaging data may contribute to more accurate and individualized cancer diagnostics.
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