title: [Semiquantitative histological evaluation of IgA nephropathy and Cox's proportional Hazzard model analysis].
abstract: In order to examine the relationship between microscopic findings and the prognosis of patients with IgA nephropathy, a multiple regression lifetable analysis was performed using a Cox's proportional Hazzard model. Histological changes were evaluated on the basis of nine parameters. By using the changes in serum creatinine concentration (S-Cr) as the criterion for assessing the prognosis, calculations were made at two points, the first point of S-Cr reached 2 mg/dl and the second of 4 mg/dl following the biopsy. As a result, the following conclusions were obtained: 1) At the S-Cr value of 2 mg/dl, two regression coefficients for mesangial lesions and crescent formations showed a correlation (P less than 0.10) with respective risk ratios of 4.517 and 9.970. 2) At the S-Cr value of 4 mg/dl, the regression coefficient for complete glomerular sclerosis was statistically significant (P less than 0.05) with a risk ratio of 6.527. Mesangial lesions and tubulo-interstitial lesions had a risk ratio ranging from 3.0 to 4.0. 3) In assessing renal histological findings in IgA nephropathy, it is important to take consideration into the variations in the severity and the stage of the renal dysfunction. 4) Although statistical significance of the pathological findings could not be achieved, such speculation as described before was made. More definitive conclusions may be attained by the longer following up on the clinical course, increasing the number of patients to be examined, and devising a more appropriate method for the evaluation of renal tissue lesions.
authors.affiliation: Department of Medicine, Kidney Center, Tokyo Women's Medical College.
authors.forename: N
authors.initials: N
authors.lastname: Nakao
mesh_terms: D005920:Glomerular Mesangium / Q000473:pathology; D005922:Glomerulonephritis, IGA / Q000401:mortality / Q000473:pathology*; D006801:Humans; D007678:Kidney Glomerulus / Q000473:pathology; D011379:Prognosis; D016016:Proportional Hazards Models; D012044:Regression Analysis; D012306:Risk