Prediction of treatment response in lupus nephritis using density of tubulointerstitial macrophage infiltration

Abstract

Background: Lupus nephritis (LN) is a common disease with diverse clinical and pathological manifestations. A major challenge in the management of LN is the inability to predict its treatment response at an early stage. The objective of this study was to determine whether the density of tubulointerstitial macrophage infiltration can be used to predict treatment response in LN and whether its addition to clinicopathological data at the time of biopsy would improve risk prediction.

Methods: In this retrospective cohort study, 430 patients with LN in our hospital from January 2010 to December 2017 were included. We used immunohistochemistry to show macrophage and lymphocyte infiltration in their biopsy specimens, followed by quantification of the infiltration density. The outcome was the treatment response, defined as complete or partial remission at 12 months of immunosuppression.

Results: The infiltration of CD68⁺ macrophages in the interstitium increased in patients with LN. High levels of CD68⁺ macrophage infiltration in the interstitium were associated with a low probability of treatment response in the adjusted analysis, and verse vice. The density of CD68⁺ macrophage infiltration in the interstitium alone predicted the response to immunosuppression (area under the curve [AUC], 0.70; 95% CI, 0.63 to 0.76). The addition of CD68⁺cells/interstitial field to the pathological and clinical data at biopsy in the prediction model resulted in an increased AUC of 0.78 (95% CI, 0.73 to 0.84).

Conclusion: The density of tubulointerstitial macrophage infiltration is an independent predictor for treatment response in LN. Adding tubulointerstitial macrophage infiltration density to clinicopathological data at the time of biopsy significantly improves risk prediction of treatment response in LN patients.

Keywords: lupus nephritis; macrophage infiltration; predictive models; predictor; treatment response.

Figure 1

Flowchart of the study.

Figure 2

Characteristics of infiltrating cells in two groups. (A, B) Representative images of immunostaining for CD4 of tubulointerstitial (×200), (C, D) immunostaining for CD8 of tubulointerstitial(×200), (E, F) immunostaining for CD68 of glomerular (×400), (G,H) immunostaining for CD68 of tubulointerstitial(×200).

Figure 3

Correlations between ISN/RPS classification in LN with CD4⁺ lymphocyte infiltration in tubulointerstitium (A), CD8⁺ lymphocyte infiltration in tubulointerstitium (B), CD68⁺ macrophage infiltration in tubulointerstitium (C), and CD68⁺ macrophage infiltration in glomeruli (D). *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Boxplot: boxplot medians (center lines), interquartile ranges (box ranges), whisker ranges; LP, lupus podocytopathy. ns, not significant.

Figure 4

The heatmap shows correlations between parameters relevant for LN among the 430 patients enrolled. Only significant p values (P < 0.05) are shown. Red and blue colors represent significant negative and positive correlations. Darker color represents stronger correlations. *P < 0.05, **P < 0.01, ***P < 0.001.WBC, white blood cell; PLT, blood platelet; Hb, hemoglobin; ALB, albumin; SCr, serum creatinine; UA, blood uric acid; UPRO, urinary protein quantitation; eGFR, estimated glomerular filtration rate; C3, complement 3; C4, complement 4; CD4, CD4⁺ cell count; CD8, CD8⁺ cell count; AIs, activity index score; CIs, chronicity index score; GN, glomerulus number.