Evidence map›Paper›PMID 35640982›Full record

Trial reportLupus science & medicine2022

Predictors of treatment response in a lupus nephritis population: lessons from the Aspreva Lupus Management Study (ALMS) trial.

Stephen McDonald, Sean Yiu, Li Su, Caroline Gordon, Matt Truman, Laura Lisk, Neil Solomons, Ian N Bruce, MASTERPLANS Consortium

Registry-linked trialOpen access · goldAbstract readClinical Trial
In one paragraph

Trial report in Lupus science & medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06228222 (Predictors of Remission and Renal Outcomes in Lupus Nephritis in Assuit University Hospitals.), which is not on this map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.0field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06228222 unknown statusnot on this mapstarted 2024, after this paper: background citation

Predictors of Remission and Renal Outcomes in Lupus Nephritis in Assuit University Hospitals.

TypeobservationalSponsorAssiut UniversityRan2024 to 2025Enrolled50ConditionsLupus Nephritis, Systemic Lupus ErythematosusArmsrenal biopsy
3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 12 citations in OpenAlex.

  1. Refractory lupus nephritis: national multicenter study.Internal and emergency medicine · 2026
    Article
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  6. Review
  7. Review
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  12. Kidney diseases in women: difference in risks and opportunities.Revista da Associacao Medica Brasileira (1992) · 2023
    Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 4 institutions in 2 countries.

Stephen McDonaldThe Kellgren Centre for Rheumatology, NIHR Manchester Biomedical Research Centre, Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.ORCID 0000-0001-7151-7654
Sean YiuMRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
Li SuMRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
Caroline GordonRheumatology Research Group, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK.
Matt TrumanAurinia Pharmaceuticals Inc, Victoria, British Columbia, Canada.
Laura LiskAurinia Pharmaceuticals Inc, Victoria, British Columbia, Canada.
Neil SolomonsAurinia Pharmaceuticals Inc, Victoria, British Columbia, Canada.
Ian N BruceThe Kellgren Centre for Rheumatology, NIHR Manchester Biomedical Research Centre, Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK ian.bruce@manchester.ac.uk.ORCID 0000-0003-3047-500X
MASTERPLANS Consortium
Aurinia (Canada) · CAManchester Academic Health Science Centre · GBUniversity of Cambridge · GBUniversity of Birmingham · GB

Funding

Medical Research Council MC_UU_00002/15Medical Research Council MR/M01665X/1
6 · The paper itself

Abstract

objectivesTo identify predictors of overall lupus and lupus nephritis (LN) responses in patients with LN.

methodsData from the Aspreva Lupus Management Study (ALMS) trial cohort was used to identify baseline predictors of response at 6 months. Endpoints were major clinical response (MCR), improvement, complete renal response (CRR) and partial renal response (PRR). Univariate and multivariate logistic regressions with least absolute shrinkage and selection operator (LASSO) and cross-validation in randomly split samples were utilised. Predictors were ranked by the percentage of times selected by LASSO and prediction performance was assessed by the area under the receiver operating characteristics (AUROC) curve.

resultsWe studied 370 patients in the ALMS induction trial. Improvement at 6 months was associated with older age (OR=1.03 (95% CI: 1.01 to 1.05) per year), normal haemoglobin (1.85 (1.16 to 2.95) vs low haemoglobin), active lupus (British Isles Lupus Assessment Group A or B) in haematological and mucocutaneous domains (0.61 (0.39 to 0.97) and 0.50 (0.31 to 0.81)), baseline damage (SDI>1 vs =0) (0.38 (0.16 to 0.91)) and 24-hour urine protein (0.63 (0.50 to 0.80)). LN duration 2-4 years (0.43 (0.19 to 0.97) vs <1 year) and 24-hour urine protein (0.63 (0.45 to 0.89)) were negative predictors of CRR. LN duration 2-4 years (0.45 (0.24 to 0.83) vs <1 year) negatively predicted PRR. The AUROCs of models for improvement, CRR and PRR were 0.56, 0.55 and 0.51 respectively.

conclusionsBaseline variables predicted 6-month outcomes in patients with SLE. While the modest performance of models emphasises the need for new biomarkers to advance this field, the factors identified can help identify those patients who may require novel treatment strategies.

Indexed as

Lupus Erythematosus, SystemicLupus NephritisCohort StudiesHemoglobinsHumansKidneyHemoglobinscyclophosphamidelupus nephritistreatment

Identifiers

PMID35640982
PMCPMC9157342
OpenAlexW4281746658

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.