Predicting long‐term trends in inflammatory neuropathy outcome measures using latent class modelling

Abstract

Immunoglobulin (Ig) is used to treat chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) and multifocal motor neuropathy with conduction block (MMNCB). Regular infusions may be used for symptom control. Disease activity is monitored with clinical outcome measurements. We examined outcome measure variation during clinically stable periods in Ig‐treated CIDP and MMNCB patients. We explored utility of serial outcome measurement in long‐term outcome prediction. Retrospective longitudinal analysis of a single neuroscience centre's Ig‐treated CIDP and MMNCB patients, 2009‐2020, was performed. Mean and percentage change for grip strength, Rasch‐built overall disability scales (RODS) and MRC sum scores (MRC‐SS) during periods of clinical stability were compared to score‐specific minimal clinically important differences (MCID). Latent class mixed modelling (LCMM) was used to identify longitudinal trends and factors influencing long‐term outcome. We identified 85 CIDP and 23 MMNCB patients (1423 datapoints; 5635 treatment‐months). Group‐averaged outcome measures varied little over time. Intra‐individual variation exceeded MCID for RODS in 44.2% CIDP and 16.7% MMNCB datapoints, grip strength in 10.6% (CIDP) and 8.8%/27.2% (MMNCB right/left hand) and MRC‐SS in 43.5% (CIDP) and 20% (MMNCB). Multivariate LCMM identified subclinical trends towards improvement (32 patients) and deterioration (73 patients) in both cohorts. At baseline, CIDP ‘deteriorators’ were older than ‘improvers’ (66.2 vs 57 years, P = .025). No other individual factors predicted categorisation. The best model for ‘deteriorator’ identification was contiguous sub‐MCID decline in more than one outcome measure (CIDP: sensitivity 74%, specificity 59%; MMNCB: sensitivity 73%, specificity 88%). Outcome measure interpretation determines therapeutic decision‐making in Ig‐dependent neuropathy patients, but intra‐individual variation is common, often exceeding MCID. Here we show sub‐MCID contiguous changes in more than one outcome measurement are a better predictor of long‐term outcome.

CIDP prognosis in patients with IVIG treatment‐related fluctuations

“…First, the small number of patients and sometimes incomplete datasets made statistical differences challenging to detect. Second, while deteriorations greater than MCID were infrequent, in some patients changes less than MCID may still be clinically meaningful and are not reflected in the arbitrary cutoff values of this study's TRF definition 8 . In clinical practice, any change in outcome should be taken on a case‐by‐case basis to determine the importance.…”

Assessing deterioration using impairment and functional outcome measures in chronic inflammatory demyelinating polyneuropathy: A post‐hoc analysis of the immunoglobulin overtreatment in CIDP trial

“…In addition, specifically applicable for our study, variability may be also influenced by blinding of patients and potential nocebo effects 15 . Recently, a retrospective study that included stable, IgG‐treated CIDP patients found that, during routine care, the MCIDs of the 4 centiles of I‐RODS, 8 kg of grip strength (using a Jamar dynamometer) and 2 points on the MRC‐SS were met in 44%, 11% and 44%, respectively 26 . This implies that variability exceeding MCIDs in stable patients is also common in clinical care.…”

“…To make further recommendations concerning MCIDs, additional research is needed to investigate the variability of scores in stable patients and investigate the accuracies and cutoffs of (combined) MCIDs for both improvement and deterioration, using larger sample sizes, in the context of both (randomized) clinical trials and clinical care, for example by means of a meta‐analysis. It is advised to combine MCIDs on the level of disability as well as impairment to assess changes 26,33 . The MCID calculations should be based primarily on relevant and multiple clinical anchors and methods, since it is unknown which anchors and methods are superior.…”

“…It is advised to combine MCIDs on the level of disability as well as impairment to assess changes. 26,33 The MCID calculations should be based primarily on relevant and multiple clinical anchors and methods, since it is unknown which anchors and methods are superior. Distribution-based methods should be used alongside clinical anchors to define the threshold beyond the random variability.…”

Pragmatic guide to peripheral nerve disease and the role of clinical biomarkers

“…For instance, NHS commissioning guidelines for IVIg use requires demonstration of improvement in disability in at least one of three outcome measures judged by the clinician to be appropriate for the patient’s disability 75. In fact, contiguous small (sub-MCID) changes in more than one outcome measure may be more specific and sensitive at identifying relevant change than larger single outcome measure changes 76…”