Skip to main content
Download PDF

Searching for a prognostic index in lupus nephritis

European Journal of Medical Research volume 28, Article number: 19 (2023) Cite this article

Abstract

Background

Currently we do not have an ideal biomarker in lupus nephritis (LN) that should help us to identify those patients with SLE at risk of developing LN or to determine those patients at risk of renal progression. We aimed to evaluate the development of a prognostic index for LN, through the evaluation of clinical, analytical and histological factors used in a cohort of lupus. We have proposed to determine which factors, 6 months after the diagnosis of LN, could help us to define which patients will have a worse evolution of the disease and may be, more aggressive treatment and closer follow-up.

Methods

A retrospective study to identify prognostic factors was carried out. We have included patients over 18 years of age with a clinical diagnosis of systemic lupus erythematosus (SLE) and kidney involvement confirmed by biopsy, who are followed up in our centre during the last 20 years. A multi-step statistical approach will be used in order to obtain a limited set of parameters, optimally selected and weighted, that show a satisfactory ability to discriminate between patients with different levels of prognosis.

Results

We analysed 92 patients with LN, although only 73 have been able to be classified according to whether or not they have presented poor renal evolution. The age of onset (44 vs. 32; p = 0.024), the value of serum creatinine (1.41 vs. 1.04; p = 0.041), greater frequency of thrombocytopenia (30 vs. 7%; p = 0.038), higher score in the renal chronicity index (2.47 vs. 1.04; p = 0.015), proliferative histological type (100%) and higher frequency of interstitial fibrosis (67 vs. 32%; p = 0.017) and tubular atrophy (67 vs. 32%; p = 0.018) was observed between two groups. The multivariate analysis allowed us to select the best predictive model for poor outcome at 6 months based on different adjustment and discrimination parameters.

Conclusion

We have developed a prognostic index of poor renal evolution in patients with LN that combines demographic, clinical, analytical and histopathological factors, easy to use in routine clinical practice and that could be an effective tool in the early detection and management.

Key messages

  1. 1.

    Development a prognostic index of poor renal evolution in patients with LN.

  2. 2.

    We use clinical, histological and laboratory factors 6 months after diagnosis and treatment

  3. 3.

    Effective tool in the early detection and management, easy to use in clinical practice

Introduction

Lupus nephritis (LN) is one of the most common manifestations of systemic lupus erythematosus (SLE), affecting approximately 40% of patients with lupus. It represents a major risk factor for morbidity and mortality, and 10% of patients with LN will develop end-stage kidney disease (ESKD) [1, 2].

The survival of patients with SLE has improved in recent decades. This improvement is due to advances in the diagnosis and treatment [3]. Despite this improvement, we currently lack good biomarkers to predict the course of lupus nephritis, the best therapeutic option or the response to treatment. Remission is achieved in 20–30% of the patients within 6–12 months from the onset of LN and 20%–35% of those patients relapse within 3–5 years. At least, 20% of LN patients develop chronic kidney disease (CKD) and 5–20% reach ESKD within 10 years from the LN onset. The management of immunosuppression utilized in LN requires highly nuanced care [4]. This reinforces the importance of early detection and treatment when looking for adequate long-term outcomes. In this way, Ayoub et al. [5] tried to develop a prediction model of treatment response in LN after 12 months of diagnosis. Early decrease in proteinuria predicts good long-term renal outcome, however, while the positive predictive value of this target was excellent, the negative predictive value was poor.

Our group have recently published a systematic review about the potential prognostic factors in LN. The main contributing factors have been serum creatinine (SCr), glomerular filtration rate (eGFR), levels of C3, C1q and anti-DNA antibodies. The histological factors that marked the evolution of renal function were class IV and V, interstitial and vascular involvement, and the chronicity index [6].

Nowadays, we do not have adequate biomarkers in clinical practice to predict the prognosis of patients with lupus nephritis. For this reason, the aim of this study was the development of a prognostic index for LN through the evaluation of clinical, analytical and histological factors used in a cohort of lupus patients in our hospital. This prognostic index should be easy to apply to routine clinical practice and be able to select those patients who would require closer monitoring to prevent the development of CKD.

Methods

This retrospective study was carried out at University Hospital “12 de Octubre”, a 1,200-bed tertiary care centre in Madrid, Spain. We selected patients ≥ 18 years diagnosed with SLE (regardless of vital status), according to the 1997 American College of Rheumatology (ACR) revised criteria [7] and kidney involvement confirmed by biopsy according to International Society of Nephrology/Renal Pathology Society (ISN/RPS) classification [8], who are followed up in our centre during the last 20 years. The institution’s Ethical and Research Committee approved the study (approval number: 17/061), including the current analysis. Participants gave informed consent to participate in the study before taking part.

Variables and measurements

Data collection were done from clinical charts and we obtained information from the following domains: (1) demographics; (2) chronological; (3) general clinical data, including vital status; (4) cumulative manifestations of SLE, defined by the glossaries of the ACR criteria for classification of SLE and an activity index, SLE Disease Activity Index (SLEDAI); (5) comorbidities, including cardiovascular risk factors and cause of death; and (6) treatments previous of LN and induction and maintenance therapy for LN. Antiphospholipid syndrome was defined according to the Sydney criteria [9].

The main variable was poor renal evolution and was defined by the presence of at least one of the following:

  • Non-response to treatment Active urine sediment, proteinuria > 0.5 g/d, impaired renal function (eGFR < 90 ml/min or deterioration > 10% compared to baseline filtration if it was altered, calculated with the estimation of glomerular filtration rate of Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) [10]).

  • Recurrences of kidney involvement Understanding recurrence as the increase in the activity of the disease that requires intensifying treatment. We defined relapse as reappearance or significant increase in haematuria (> 15 red cells/field) with dysmorphic red cells and/or casts and/or sustained increase in proteinuria (≥ 1 g/24 h or ≥ 1 g/g in patients with complete remission or ≥ 50% of baseline proteinuria in patients with partial remission) and/or a decrease in eGFR ≥ 25% not attributable to other causes [11].

  • Renal failure Defined according to Systemic Lupus International Collaborating Centers (SLICC) criteria [12] for chronic renal damage as creatinine clearance (estimated/measured) < 50%, proteinuria ≥ 3.5 g/24 h or end-stage renal disease (regardless of dialysis or kidney transplant) maintained for 6 months.

As independent variables, all the potential prognostic factors, as well as the possible confounding factors and the usual descriptive variables, were collected from the clinical history. The following independent variables were used:

  • Demographics: age at onset of nephritis, gender, and ethnicity.

  • Cardiovascular risk factors prior to nephritis.

  • Lupus activity: extrarenal manifestations and baseline SLEDAI [13].

  • Serological activity: anti-dsDNA antibodies by IFI; antiphospholipid profile (lupus anticoagulant (LA) positive (based on aPPT, silica test or dRVVT) or anticardiolipin (ACL) IgG and/or IgM or—antiB2glycoprotein (aB2GP1) IgG or IgM) > 40 UFL/ml; low C3 (< 83 mg/dl); low C4 (< 14 mg/dl).

  • Analytical data of kidney involvement: SCr, eGFR, 24-h proteinuria, uPCR, haematuria.

  • Histological data: activity index, chronicity index, histological type, interstitial fibrosis, tubular atrophy and thrombotic microangiopathy (TMA). Pathologic lesions were evaluated according to the International Society of Nephrology and the Renal Pathology Society (ISN/RPS) systems Austin system of semiquantitative scores for activity and chronicity was applied (Table 1) [14].

Table 1 Scores for activity and chronicity (Austin system)
Full size table

Statistic analysis

A multi-step statistical approach will be used in order to obtain a limited set of parameters, optimally selected and weighted, that show a satisfactory ability to discriminate between patients with different levels of prognosis.

Continuous variables were tested for normality to decide which type of hypothesis tests to use. The only one that presented normal distribution was glomerular filtration rate, and in this case Student's t-test was used. The rest of the continuous variables did not present normality criteria, so the Mann–Whitney U test was used.

Creation of the dependent variable “poor renal evolution”

A combined variable will be constructed in which poor renal evolution at 6 months, defined by the existence of at least one of the following situations:

  • Recurrence of kidney involvement.

  • Chronic kidney disease presence.

  • Need for dialysis or transplant.

  • Lack of response to treatment.

Description of the analysis sample and comparison of patients with and without poor renal evolution

A descriptive study of the baseline situation of the patients will be carried out, both globally and by both groups. For the description, measures of central tendency and dispersion will be used, as well as tables of frequencies and distribution of percentages for quantitative and qualitative variables, respectively. For the comparison of the groups with and without poor renal evolution, parametric or non-parametric hypothesis contrast tests will be used depending on the distribution of the variables.

Bivariate analysis

The association between prognostic factors and poor renal outcome will be studied using bivariate logistic regression models using poor renal outcome as the dependent variable and the prognostic factors described in the literature and defined by the panel of experts as independent variables.

Multivariate analysis

The predictive model will be estimated using multivariate logistic regression models, introducing into the model the prognostic factors with theoretical meaning and those that present a p value of less than 0.250 in the bivariate analysis. Successive models will be built until reaching the most parsimonious and with the lowest Akaike and Bayesian information criteria (AIC and BIC). The discrimination power of the model will be quantified by the area under the ROC curve of the final logistic model. Discriminatory power is defined as the model's ability to correctly classify subjects according to whether or not they have poor renal outcomes.

Results

Baseline characteristics

The sample has 92 patients with LN, although only 73 have been able to be classified according to whether or not they have presented poor renal evolution due to missing data. The majority are women (82%), of Caucasian ethnicity (70%) and a mean age at the onset of LN of 34 ± 15 years. The patients present mean SLEDAI values of 16 ± 7; SCr 1.12 ± 0.8 mg/dl; eGFR 84.3 ± 4.7 ml/min/1.73m2, proteinuria 3.51 ± 3.45 g/24 h and mean values in the indices of renal activity and chronicity of 4.56 ± 3.84 and 1.34 ± 1.59, respectively. 75% of patients have extrarenal manifestations, and 11% thrombocytopenia. The most frequent histological types (78%) are the proliferative forms (types III or IV or a combination with type V). Most patients do not have interstitial fibrosis (62%) or tubular atrophy (66%). From a serological point of view, 76% had anti-DNA antibodies, 29% anticardiolipin antibodies, and 20% lupus anticoagulant. In addition, there are low values of complement C3 and C4 in 67% and 64% of cases, respectively. Finally, the most used prior treatment was steroids (60%).

A description of the total sample at baseline was made and the baseline status of the groups with and without poor renal progression at 6 months was compared (Table 2).

Table 2 Baseline characteristics: total and by renal evolution at 6 months
Full size table

Evolution of patients depending on poor renal outcomes

The main differences between the two groups at six months were age of onset (44 vs. 32; p = 0.024), SCr higher values (1.41 vs. 1.04; p = 0.041), higher score in the renal chronicity index (2.47 vs. 1.04; p = 0.015), greater frequency of thrombocytopenia (30 vs. 7%; p = 0.038), proliferative histological type (100%) and higher frequency of interstitial fibrosis (67 vs. 32%; p = 0.017) and tubular atrophy (67 vs. 32%; p = 0.018) (Table 1).

The results of the bivariate analysis showed that the factors that increase the probability of poor renal evolution at 6 months are the patient's age (OR = 1.05; p = 0.020), the highest score in the renal chronicity index (OR = 1.67; p = 0.006), the presence of interstitial fibrosis (OR = 4.44; p = 0.016) or tubular atrophy (OR = 4.33; p = 0.018) and the thrombocytopenia platelets < 50,000 per mm3) (OR = 5.67; p = 0.029) (Table 3).

Table 3 Predictors of poor renal evolution at 6 months
Full size table

The multivariate analysis allowed us to select the 3 best predictive models for poor outcome at 6 months based on different adjustment and discrimination parameters (Table 4). The areas under the ROC curve (AUC) obtained in this model, ranged between 0.897 and 0.899, with no statistically significant differences (Fig. 1). The predicted probability cut-off point was chosen by the model that maximized the values of sensitivity (correct classification of poor outcomes), specificity (correct classification of negatives) and the percentage of global classification. The main predictors of poor renal evolution were thrombocytopenia, with OR greater than 30, and interstitial fibrosis, with OR greater than 20, although in both cases the confidence intervals were very wide (Table 4).

Table 4 Predictive models of poor evolution at 6 months
Full size table
Fig. 1
figure 1

Comparison of ROC curves of the selected models: 6 months

Full size image

The model chosen for poor outcome at 6 months is shown in Table 5. In equality of sensitivity and specificity, we have chosen the model with the highest predicted probability. We have analysed prognosis factors of poor outcomes in LN at 12 months, but this will be discussed in another paper.

Table 5 Predictive model of poor evolution at 6 months
Full size table

Discussion

In this retrospective study in patients with LN, we have designed a prognostic index for evolution of renal function in patients with lupus nephritis. The main predictors of poor renal evolution were thrombocytopenia and interstitial fibrosis. Our findings highlight the value of thrombocytopenia and histology to determine renal survival in patients with LN.

In our study, older patients (44.4 ± 19.1 years) had worst evolution renal function compared with younger patients (32.2 ± 13.9 years). Kang et al. [15] found similar results in 117 patients with LN followed during follow-up during a mean of 76.5 months. They divided them into three groups based on age: juvenile LN (JLN) if < 8 years old, adult LN (ALN) between 18 and 50 years old and late-onset LN (LLN) if > 50 years old. The study findings showed that the patients with LLN had a higher chronicity index, developed CKD and death higher than JLN and ALN patients.

Several studies have shown that tubular atrophy and interstitial fibrosis were independent factors for poor renal evolution [16,17,18,19,20,21,22,23] as well as the chronicity index [24]. Tang et al. [25] have developed and validated a risk score for the development of ESRD in LN, emphasizing the importance of tubulointerstitial lesions (tubular atrophy and interstitial fibrosis) than the histological subtype according to the ISN/RPS classification [26]. These renal histopathological changes will be considered a chronic change and loss of function of the nephrons and therefore they are related to the poor renal evolution. Ayoub et al. [5] have developed a prediction model of treatment in LN, showing that early detection and treatment of NL was essential to achieve good long-term renal outcomes. In this predictive model they have used classical biomarkers (proteinuria, renal glomerular filtration rate) and new urinary biomarkers (cytokines, chemokines). This study has showed that the predictive value of proteinuria in LN is complicated because proteinuria may represent acute kidney injury due to inflammation and podocyte dysfunction, or chronic kidney injury due to scarring after inflammation. However, clinical and demographic variables were relatively more important than any novel urine biomarker.

A recent systematic review by our group on the main prognostic factors in the outcome of CKD has shown that the classical biomarkers (proteinuria, GFR and urinary sediment) remain despite advances in the diagnosis and treatment of lupus nephritis [6]. One of the main limitations of clinical trials in LN has been considering renal function and proteinuria as the only criteria for assessing response to treatment. However, the concept of a histopathological target emerged from observations that clinical outcome based on proteinuria and/or urinalysis and histopathological outcome based on repeat kidney biopsies are discordant. Recent studies have shown that an activity and chronicity index > 3 correlates with a higher incidence of relapse and CKD, respectively, in lupus nephritis [27]. The nuances of histological lesions have become a cornerstone of the evolution of renal function. Several publications have shown that chronic damage in the tubulointerstitial compartment and different kinds of vascular lesions contributed significantly to the association with poor long-term renal function [21,22,23, 28, 29]. Korbet et al. [18] have showed a significant association between the evidence of irreversible kidney damage (renal sclerosis, tubular atrophy, or interstitial fibrosis) with the negative impact on achieving remission.

We recently showed that histological findings in repeat kidney biopsies of LN patients commonly present discordance in relation to clinical expression. At repeat biopsy, chronicity index was more influential over CKD progression than the shift to lower pathological classes [27, 30]. Histological data from repeat kidney biopsies in LN could be useful to guide therapeutic approach [27]. For this reason, prospective randomized studies such as "Per-protocol repeat kidney biopsy in incident cases of LN" should shed some more light on the possibility of changing the course of lupus nephritis.

In the present study, the presence of thrombocytopenia below 50,000 cells/mm3 has been identified as an important risk factor for the progression of renal damage. The finding of thrombocytopaenia was not in the context of a manifestation associated with thrombotic microangiopathy, but as a more severe extrarenal systemic manifestation of systemic lupus erythematosus. Clark et al. observed that kinetic studies performed in patients with SLE have shown evidence of platelet consumption in the majority, and it is agreed by most authors that patients with SLE demonstrate evidence of compensated thrombocytolysis [31]. In the past this had been thought to relate to the presence of a circulating antibody to platelets [32, 33], but more recent evidence supports the hypothesis of the antiplatelet factor in SLE being a circulating immune complex [32, 34, 35]. Hence thrombocytopenia may reflect interaction of the platelet with an immune complex of critical size or configuration, which results in tissue damage and associated disease activity [36]. The presence of thrombocytopenia at the debut of SLE should alert us to a worse evolution of patients with lupus nephritis, and therefore we should try to be more forceful in our immunosuppressive treatment. Haematological abnormalities, especially thrombocytopenia, are highly prevalent among patients with systemic lupus erythematosus and at the same time it has been reported as a significant prognostic factor of SLE course [37]. Several studies have shown that the significance platelet count has a negative correlation with disease activity in SLE patients (arthritis, neurologic manifestations, and nephritis), whatever the associated manifestations, and it should be considered as a prognostic factor, identifying patients with aggressive disease course [36,37,38].

This study is subject to limitations due to the small sample size and its single-centre retrospective nature. However, strengths include that it is a real-world experience in standard clinical practice and a long follow-up time, giving homogeneity to our histological results. Our predictive model shows good discrimination capacity, with area under the curve close to 0.9.

Our study suggests that this prognosis index may be useful in clinical practice to detect which patients with lupus nephritis may have a worse renal prognosis and to modify our therapeutic approach to preserve kidney function. In order to stratify patients into different risk grades, future research is needed for internal and external validation with another cohort of patients.

In conclusion, we have developed a prognostic index of poor renal evolution in patients with LN that combines demographic, clinical, analytical and histopathological factors, easy to use in routine clinical practice and that could be an effective tool in the early detection and management of patients.

Data availability

Not applicable.

Abbreviations

aB2GP1:

Anti-B2 glycoprotein1

ACL:

Anticardiolipin

ACR:

American College of Rheumatology

AIC and BIC:

Akaike and Bayesian information criteria

CKD:

Chronic kidney disease

CKD-EPI:

Chronic Kidney Disease Epidemiology Collaboration

eGFR:

Glomerular filtration rate

ESKD:

End-stage kidney disease

ISN/RNP:

International Society of Nephrology/Renal Pathology Society

LA:

Lupus anticoagulant

LN:

Lupus nephritis

SCr:

Serum creatinine

SLE:

Systemic Lupus Erythematosus

SLEDAI:

Systemic Lupus Erythematosus Disease Activity Index

SLICC:

Systemic Lupus International Collaborating Centers

uPCR:

Urine protein/creatinine rate

TMA:

Thrombotic microangiopathy

References

  1. Morales E, Galindo M, Trujillo H, Praga M. Update on lupus nephritis: looking for a new vision. Nephron. 2021;145(1):1–13.

    Article  Google Scholar 

  2. Tektonidou MG, Dasgupta A, Ward MM. Risk of end-stage renal disease in patients with lupus Nephritis, 1971–2015: a systematic review and Bayesian meta-analysis: ESRD RISK IN LUPUS NEPHRITIS. Arthritis Rheumatol. 2016;68(6):1432–41.

    Article  Google Scholar 

  3. Bomback AS. An update on therapies for proliferative lupus nephritis: how certain can we be about the evidence? Am J Kidney Dis. 2018;72(5):758–60.

    Article  Google Scholar 

  4. Parodis I, Ding H, Zickert A, Arnaud L, Larsson A, Svenungsson E, et al. Serum soluble tumour necrosis factor receptor-2 (sTNFR2) as a biomarker of kidney tissue damage and long-term renal outcome in lupus nephritis. Scand J Rheumatol. 2017;46(4):263–72.

    Article  CAS  Google Scholar 

  5. Ayoub I, Wolf BJ, Geng L, Song H, Khatiwada A, Tsao BP, et al. Prediction models of treatment response in lupus nephritis. Kidney Int. 2022;101(2):379–89.

    Article  CAS  Google Scholar 

  6. Rodríguez-Almaraz E, Gutiérrez-Solís E, Rabadán E, Rodríguez P, Carmona L, Morales E, et al. Something new about prognostic factors for lupus nephritis? A systematic review. Lupus. 2021;30(14):2256–67.

    Article  Google Scholar 

  7. Hochberg MC. Updating the American College of Rheumatology revised criteria for the classification of systemic lupus erythematosus. Arthritis Rheum. 1997;40(9):1725.

    Article  CAS  Google Scholar 

  8. Weening JJ, D’Agati VD, Schwartz MM, Seshan SV, Alpers CE, Appel GB, et al. The classification of glomerulonephritis in systemic lupus erythematosus revisited. Kidney Int. 2004;65(2):521–30.

    Article  Google Scholar 

  9. Miyakis S, Lockshin MD, Atsumi T, Branch DW, Brey RL, Cervera R, et al. International consensus statement on an update of the classification criteria for definite antiphospholipid syndrome (APS). J Thromb Haemost. 2006;4(2):295–306.

    Article  CAS  Google Scholar 

  10. Levey AS, Stevens LA, Schmid CH, Zhang Y (Lucy), Castro AF, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604.

  11. Rojas-Rivera JE, García-Carro C, Ávila AI, Espino M, Espinosa M, Fernández-Juárez G, et al. Documento de consenso del Grupo de Estudio de Enfermedades Glomerulares de la Sociedad Española de Nefrología (GLOSEN) para el diagnóstico y tratamiento de la nefritis lúpica. Nefrología. 2022;S021169952200159X.

  12. Aringer M, Petri M. New classification criteria for systemic lupus erythematosus. Curr Opin Rheumatol. 2020;32(6):590–6.

    Article  CAS  Google Scholar 

  13. Yee C, Gordon C, Isenberg DA, Griffiths B, Teh L, Bruce IN, et al. Comparison of responsiveness of BILAG-2004, SLEDAI-2000 and BILAG Systems Tally (BST). Arthritis Care Res. 2021. https://doi.org/10.1002/acr.24606.

    Article  Google Scholar 

  14. Austin HA, Muenz LR, Joyce KM, Antonovych TA, Kullick ME, Klippel JH, et al. Prognostic factors in lupus nephritis. Am J Med. 1983;75(3):382–91.

    Article  Google Scholar 

  15. Kang JH, Park DJ, Lee KE, Lee JS, Choi YD, Lee SS. Comparison of clinical, serological, and prognostic differences among juvenile-, adult-, and late-onset lupus nephritis in Korean patients. Clin Rheumatol. 2017;36(6):1289–95.

    Article  Google Scholar 

  16. Zhang J, Song H, Li D, Lv Y, Chen B, Zhou Y, et al. Role of clinicopathological features for the early prediction of prognosis in lupus nephritis. Immunol Res. 2021;69(3):285–94.

    Article  CAS  Google Scholar 

  17. Obrișcă B, Jurubiță R, Andronesi A, Sorohan B, Achim C, Bobeica R, et al. Histological predictors of renal outcome in lupus nephritis: the importance of tubulointerstitial lesions and scoring of glomerular lesions. Lupus. 2018;27(9):1455–63.

    Article  Google Scholar 

  18. Korbet SM, Lewis EJ, Schwartz MM, Reichlin M, Evans J, Rohde RD. Factors predictive of outcome in severe lupus nephritis. Lupus Nephritis Collaborative Study Group. Am J Kidney Dis. 2000;35(5):904–14.

    Article  CAS  Google Scholar 

  19. Yang XW, Tan Y, Yu F, Zhao MH. Combination of anti-C1q and anti-dsDNA antibodies is associated with higher renal disease activity and predicts renal prognosis of patients with lupus nephritis. Nephrol Dial Transplant. 2012;27(9):3552–9.

    Article  CAS  Google Scholar 

  20. Dall’Era M, Levesque V, Solomons N, Truman M, Wofsy D. Identification of clinical and serological factors during induction treatment of lupus nephritis that are associated with renal outcome. Lupus Sci Med. 2015;2(1):e000089.

    Article  Google Scholar 

  21. Alsuwaida A. Interstitial inflammation and long-term renal outcomes in lupus nephritis. Lupus. 2013;22(14):1446–54.

    Article  CAS  Google Scholar 

  22. Faurschou M, Starklint H, Halberg P, Jacobsen S. Prognostic factors in lupus nephritis: diagnostic and therapeutic delay increases the risk of terminal renal failure. J Rheumatol. 2006;33(8):1563–9.

    Google Scholar 

  23. Franco C, Yoo W, Franco D, Xu Z. Predictors of end stage renal disease in African Americans with lupus nephritis. Bull NYU Hosp Jt Dis. 2010;68(4):251–6.

    Google Scholar 

  24. Umeda R, Ogata S, Hara S, Takahashi K, Inaguma D, Hasegawa M, et al. Comparison of the 2018 and 2003 International Society of Nephrology/Renal Pathology Society classification in terms of renal prognosis in patients of lupus nephritis: a retrospective cohort study. Arthritis Res Ther. 2020;22(1):260.

    Article  CAS  Google Scholar 

  25. Tang Y, Zhang X, Ji L, Mi X, Liu F, Yang L, et al. Clinicopathological and outcome analysis of adult lupus nephritis patients in China. Int Urol Nephrol. 2015;47(3):513–20.

    Article  Google Scholar 

  26. Bajema IM, Wilhelmus S, Alpers CE, Bruijn JA, Colvin RB, Cook HT, et al. Revision of the International Society of Nephrology/Renal Pathology Society classification for lupus nephritis: clarification of definitions, and modified National Institutes of Health activity and chronicity indices. Kidney Int. 2018;93(4):789–96.

    Article  Google Scholar 

  27. Parodis I, Adamichou C, Aydin S, Gomez A, Demoulin N, Weinmann-Menke J, et al. Per-protocol repeat kidney biopsy portends relapse and long-term outcome in incident cases of proliferative lupus nephritis. Rheumatology (Oxford). 2020;59(11):3424–34.

    Article  CAS  Google Scholar 

  28. Barber C, Herzenberg A, Aghdassi E, Su J, Lou W, Qian G, et al. Evaluation of clinical outcomes and renal vascular pathology among patients with lupus. Clin J Am Soc Nephrol. 2012;7(5):757–64.

    Article  Google Scholar 

  29. Hernandez-Molina G, García-Trejo LP, Uribe N, Cabral AR. Thrombotic microangiopathy and poor renal outcome in lupus patients with or without antiphospholipid syndrome. Clin Exp Rheumatol. 2015;33(4):503–8.

    Google Scholar 

  30. Moroni G, Porata G, Raffiotta F, Frontini G, Calatroni M, Reggiani F, et al. Predictors of increase in chronicity index and of kidney function impairment at repeat biopsy in lupus nephritis. Lupus Sci Med. 2022;9(1): e000721.

    Article  Google Scholar 

  31. Garg SK, Amorosi EL, Karpatkin S. Use of the Megathrombocyte as an Index of Megakaryocyte Number. N Engl J Med. 1971;284(1):11–7.

    Article  CAS  Google Scholar 

  32. Karpatkin S, Strick N, Karpatkin MB, Siskind GW. Cumulative experience in the detection of antiplatelet antibody in 234 patients with idiopathic thrombocytopenic purpura, systemic lupus erythematosus and other clinical disorders. Am J Med. 1972;52(6):776–85.

    Article  CAS  Google Scholar 

  33. Karpatkin S, Siskind GW. In vitro detection of platelet antibody in patients with idiopathic thrombocytopenic purpura and systemic lupus erythematosus. Blood. 1969;33(6):795–812.

    Article  CAS  Google Scholar 

  34. Budman DR. Hematologic aspects of systemic lupus erythematosus: current concepts. Ann Intern Med. 1977;86(2):220.

    Article  CAS  Google Scholar 

  35. Clark WF, Lewis ML, Cameron JS, Parsons V. Intrarenal platelet consumption in the diffuse proliferative nephritis of systemic lupus erythematosus. Clin Sci. 1975;49(3):247–52.

    Article  CAS  Google Scholar 

  36. Clark WF, Friesen M, Linton AL, Lindsay RM. The platelet as a mediator of tissue damage in immune complex glomerulonephritis. Clin Nephrol. 1976;6(1):287–9.

    CAS  Google Scholar 

  37. Abdel Galil SM, Edrees AM, Ajeeb AK, Aldoobi GS, El-Boshy M, Hussain W. Prognostic significance of platelet count in SLE patients. Platelets. 2017;28(2):203–7.

    Article  CAS  Google Scholar 

  38. Clark WF, Linton AL, Cordy PE, Keown PE, Lohmann RC, Lindsay RM. Immunologic findings, thrombocytopenia and disease activity in lupus nephritis. Can Med Assoc J. 1978;118(11):1391–5.

    CAS  Google Scholar 

Download references

Acknowledgements

None.

The results presented in this paper have not been published previously in whole or part, except in abstract format.

Funding

This work was supportred by: E.M. holds a research grant (2017/0122) “Desarrollo de un índice de gravedad en la Nefritis Lúpica” from Fundación Madrileña de Nefrología. M.G. holds a research grant (2017/0030) “Desarrollo de un índice de gravedad en la Nefritis Lúpica” from Sociedad de Reumatología de la Comunidad de Madrid.

Author information

Author notes

  1. E. Morales and M. Galindo-Izquierdo co-senior authors

Authors and Affiliations

  1. Department of Rheumatology, University Hospital “12 de Octubre”, Avda. Córdoba Km 5.400, 28041, Madrid, Spain

    E. Rodríguez-Almaraz, E. Rabadán & M. Galindo-Izquierdo

  2. Department of Nephrology, University Hospital “12 de Octubre”, Madrid, Spain

    E. Gutiérrez-Solís, P. Rodríguez & E. Morales

  3. Department of Pathology, University Hospital “12 de Octubre”, Madrid, Spain

    M. Alonso

  4. Instituto de Salud Musculoesquelética (Inmusc), Madrid, Spain

    L. Carmona & M. J. García de Yébenes

  5. Research Institute of University Hospital “12 de Octubre” (imas12), Madrid, Spain

    E. Rodríguez-Almaraz, E. Gutiérrez-Solís, E. Morales & M. Galindo-Izquierdo

  6. Department of Medicine, Complutense University, Madrid, Spain

    E. Morales & M. Galindo-Izquierdo

Authors
  1. E. Rodríguez-Almaraz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. E. Gutiérrez-Solís
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. E. Rabadán
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. P. Rodríguez
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. M. Alonso
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. L. Carmona
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. M. J. García de Yébenes
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. E. Morales
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. M. Galindo-Izquierdo
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All the authors contributed equally to this study, revised the paper and approved the final version of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to E. Rodríguez-Almaraz.

Ethics declarations

Competing interests

The authors have no conflicts of interest to declare.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Rodríguez-Almaraz, E., Gutiérrez-Solís, E., Rabadán, E. et al. Searching for a prognostic index in lupus nephritis. Eur J Med Res 28, 19 (2023). https://doi.org/10.1186/s40001-022-00946-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s40001-022-00946-y

Keywords

  • Lupus nephritis
  • Prognostic index
  • Poor renal evolution

European Journal of Medical Research

ISSN: 2047-783X

Contact us