Application of logistic regression in combination with multiple diagnostic tests for auxiliary diagnosis of nasopharyngeal carcinoma.
OBJECTIVE
Although there are many markers for the clinical diagnosis of nasopharyngeal carcinoma (NPC), the efficacy of most of the markers for the early diagnosis is poor. This study was to evaluate the diagnostic value of VCA/IgA, EA/IgA, EBV DNA, EBNA1/IgA, EBNA1/IgG and ZTA/IgG for NPC, as well as to screen out an optimized combination using the logistic regression to increase diagnostic accuracy of NPC.


METHODS
Eight-one newly pathologically diagnosed NPC patients prior to treatment and 89 health cases from routine physical checkups were entered into the study. Epstein-Barr virus (EBV) DNA was detected by quantitative real-time PCR; VCA/IgA and EA/IgA were assessed by immunofluorescence assays (IFA). The receiver operating characteristic (ROC) curve and the area under the curve were used to evaluate the diagnostic value of a single test or combined tests for NPC, thus to decide the cut-off value. The logistic regression model was used to combine the results from multiple tests to increase diagnostic accuracy.


RESULTS
Comparing to the routine parallel sequential test, the logistic regression in combination with multiple diagnostic tests achieved higher diagnostic specificity and sensitivity for NPC. Two optimal combinations were EBV DNA + EBNA1/IgA and VCA/IgA + EBNA1/IgA, whose sensitivity and specificity reached 0.96 and 0.82, 1.00 and 0.84, respectively. When the logistic model was used and the cut-off value was determined by ROC, the sensitivity and specificity of the two combination groups became 1.00 and 0.87, 0.98 and 0.88, respectively.


CONCLUSIONS
Adopting the logistic regression in combination with multiple diagnostic tests and using the probability prediction to decide the cut-off value may help increase the diagnostic sensitivity and specificity for NPC.
Jiang
Shi-Qiang
SQ
Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, PR China.
Liu
Qing
Q
D000293:Adolescent; D000328:Adult; D000368:Aged; D000914:Antibodies, Viral / Q000276:immunology; D000956:Antigens, Viral / Q000276:immunology; D036022:Capsid Proteins / Q000276:immunology; D004279:DNA, Viral / Q000032:analysis; D004797:Enzyme-Linked Immunosorbent Assay; D020031:Epstein-Barr Virus Infections / Q000821:virology*; D019309:Epstein-Barr Virus Nuclear Antigens / Q000276:immunology; D005260:Female; D005455:Fluorescent Antibody Technique; D004854:Herpesvirus 4, Human / Q000235:genetics / Q000276:immunology; D006801:Humans; D007070:Immunoglobulin A / Q000276:immunology; D007074:Immunoglobulin G / Q000276:immunology; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009303:Nasopharyngeal Neoplasms / Q000175:diagnosis* / Q000821:virology; D016133:Polymerase Chain Reaction / Q000379:methods; D012680:Sensitivity and Specificity; D015534:Trans-Activators / Q000276:immunology; D014764:Viral Proteins / Q000276:immunology; D055815:Young Adult
D000914:Antibodies, Viral; D000956:Antigens, Viral; C063676:BZLF1 protein, Herpesvirus 4, Human; D036022:Capsid Proteins; D004279:DNA, Viral; C402641:EBNA-2 protein, Human herpesvirus 4; D019309:Epstein-Barr Virus Nuclear Antigens; C041788:Epstein-Barr viral capsid antigen; D007070:Immunoglobulin A; D007074:Immunoglobulin G; D015534:Trans-Activators; D014764:Viral Proteins; C417029:EBV-encoded nuclear antigen 1