ImportanceAlthough IgA nephropathy (IgAN) is the most common glomerulonephritis in the world, there is no validated tool to predict disease progression. This limits patient-specific risk... Show moreImportanceAlthough IgA nephropathy (IgAN) is the most common glomerulonephritis in the world, there is no validated tool to predict disease progression. This limits patient-specific risk stratification and treatment decisions, clinical trial recruitment, and biomarker validation. ObjectiveTo derive and externally validate a prediction model for disease progression in IgAN that can be applied at the time of kidney biopsy in multiple ethnic groups worldwide. Design, Setting, and ParticipantsWe derived and externally validated a prediction model using clinical and histologic risk factors that are readily available in clinical practice. Large, multi-ethnic cohorts of adults with biopsy-proven IgAN were included from Europe, North America, China, and Japan. Main Outcomes and MeasuresCox proportional hazards models were used to analyze the risk of a 50% decline in estimated glomerular filtration rate (eGFR) or end-stage kidney disease, and were evaluated using the R-D(2) measure, Akaike information criterion (AIC), C statistic, continuous net reclassification improvement (NRI), integrated discrimination improvement (IDI), and calibration plots. ResultsThe study included 3927 patients; mean age, 35.4 (interquartile range, 28.0-45.4) years; and 2173 (55.3%) were men. The following prediction models were created in a derivation cohort of 2781 patients: a clinical model that included eGFR, blood pressure, and proteinuria at biopsy; and 2 full models that also contained the MEST histologic score, age, medication use, and either racial/ethnic characteristics (white, Japanese, or Chinese) or no racial/ethnic characteristics, to allow application in other ethnic groups. Compared with the clinical model, the full models with and without race/ethnicity had better R-D(2) (26.3% and 25.3%, respectively, vs 20.3%) and AIC (6338 and 6379, respectively, vs 6485), significant increases in C statistic from 0.78 to 0.82 and 0.81, respectively (Delta C, 0.04; 95% CI, 0.03-0.04 and Delta C, 0.03; 95% CI, 0.02-0.03, respectively), and significant improvement in reclassification as assessed by the NRI (0.18; 95% CI, 0.07-0.29 and 0.51; 95% CI, 0.39-0.62, respectively) and IDI (0.07; 95% CI, 0.06-0.08 and 0.06; 95% CI, 0.05-0.06, respectively). External validation was performed in a cohort of 1146 patients. For both full models, the C statistics (0.82; 95% CI, 0.81-0.83 with race/ethnicity; 0.81; 95% CI, 0.80-0.82 without race/ethnicity) and R-D(2) (both 35.3%) were similar or better than in the validation cohort, with excellent calibration. Conclusions and RelevanceIn this study, the 2 full prediction models were shown to be accurate and validated methods for predicting disease progression and patient risk stratification in IgAN in multi-ethnic cohorts, with additional applications to clinical trial design and biomarker research. Show less
Maps depicting the structure of science help us understand the development of science and technology. However, as it is difficult to apply inter-citation and co-citation analysis to recently... Show moreMaps depicting the structure of science help us understand the development of science and technology. However, as it is difficult to apply inter-citation and co-citation analysis to recently published papers and ongoing projects that have few or no references, our previous work developed a content-based map by locating research papers and funding projects using word/document embedding. Because difficulties arise when comparing the content-based map in different languages, this paper improves our content-based map by developing a method for generating multi-dimensional vectors in the same space from cross-lingual (English and Japanese) documents. Using 1,000 IEEE papers, we confirmed a similarity of 0.76 for matching bilingual contents. Finally, we constructed a map from 34,000 projects of the National Science Foundation and Japan Society for the Promotion of Science from 2012 to 2015, and we indicate the findings obtained from a comparison of the US-Japan funded projects. Show less
To study the predictive value of biopsy lesions in IgA nephropathy in a range of patient ages we retrospectively analyzed the cohort that was used to derive a new classification system for IgA... Show moreTo study the predictive value of biopsy lesions in IgA nephropathy in a range of patient ages we retrospectively analyzed the cohort that was used to derive a new classification system for IgA nephropathy. A total of 206 adults and 59 children with proteinuria over 0.5 g/24h/1.73 m(2) and an eGFR of stage-3 or better were followed for a median of 69 months. At the time of biopsy, compared with adults children had a more frequent history of macroscopic hematuria, lower adjusted blood pressure, and higher eGFR but similar proteinuria. Although their outcome was similar to that of adults, children had received more immunosuppressants and achieved a lower follow-up proteinuria. Renal biopsies were scored for variables identified by an iterative process as reproducible and independent of other lesions. Compared with adults, children had significantly more mesangial and endocapillary hypercellularity, and less segmental glomerulosclerosis and tubulointerstitial damage, the four variables previously identified to predict outcome independent of clinical assessment. Despite these differences, our study found that the cross-sectional correlation between pathology and proteinuria was similar in adults and children. The predictive value of each specific lesion on the rate of decline of renal function or renal survival in IgA nephropathy was not different between children and adults. Kidney International (2010) 77, 921-927; doi: 10.1038/ki.2010.43; published online 3 March 2010 Show less
