Kidney Outcomes in Self-Reported Black Patients with Primary Membranous Nephropathy in the Cure Glomerulonephropathy Study (CureGN)
Bibliographic record
Abstract
Background: Primary membranous nephropathy (pMN) is a common cause of nephrotic syndrome in adults. Disease progression in Black versus non-Black patients with pMN remains to be fully characterized. Methods: CureGN is an ongoing multi-center prospective, observational cohort of children and adults with biopsy-proven pMN or 3 other primary glomerular diseases. First diagnostic biopsies were performed between 2010 and 2023. For this analysis, we report baseline clinical data at enrollment, proportion of time on immunosuppression during follow-up, and incident rates for kidney failure and 40% eGFR decline. Time to kidney outcomes was estimated using adjusted Cox proportional hazards models. Results: As of May 2023, 608 pMN patients were enrolled (580 with available follow-up data). Of those, 93 were self-reported Black/African American race: median age 52 (IQR, 37-64); 39% female; and median follow-up time of 4.4 yrs. Among 444 pMN patients genetically sequenced, 12 (3%) had 2-high risk APOL1 alleles; of the 73 pMN patients with self-reported Black/African American race who were sequenced, 11 (15%) had 2-high risk APOL1 alleles. Conclusions: In patients with pMN, self-reported Black race appears to be strongly associated with worse kidney outcomes despite having similar eGFR at enrollment. Additional analyses including assessment of genetic factors are underway to gain understanding of determinants of this observed association. Funding: NIDDK Support - Black (N=93) Non-Black (N=515) Median eGFR at enrollment (mL /min/1.73m2)(IQR) 76.5 (51.2-103.9) 78.4 (52.6-101.0) Median urine protein to creatinine ratio at enrollment (IQR) 4.3 (1.5-8.2) 2.7 (0.7-6.3) Proportion of time on any immunosuppression during study follow up (%) 27 28 Kidney failure rate (per participant year) 0.053 0.016 eGFR decline >40% rate (per participant year) 0.082 0.033 Kidney outcomes (Black vs. Non-Black) HR (95% CI) p-value Kidney Failure 3.3 (1.6-6.6) 0.0008 Kidney Failure & eGFR decline >40% 2.4 (1.4-3.9) 0.0007 Complete Remission* 0.7 (0.4-1.1) 0.1 All models are adjusted for sex, age at biopsy, immunosuppression use prior to biopsy, UPCR at enrollment, eGFR at enrollment and time from biopsy to enrollment. *Among those who entered the study not in complete remission. eGFR = estimated glomerular filtration rate (per CKiD-U25 if age <25 years or CKD-EPI-2021).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".