Evaluation and construction of diagnostic criteria for inclusion body myositis

Thomas E Lloyd, Andrew L Mammen, Anthony A Amato, Michael D Weiss, Merrilee Needham, Steven A Greenberg, Thomas E Lloyd, Andrew L Mammen, Anthony A Amato, Michael D Weiss, Merrilee Needham, Steven A Greenberg

Abstract

Objective: To use patient data to evaluate and construct diagnostic criteria for inclusion body myositis (IBM), a progressive disease of skeletal muscle.

Methods: The literature was reviewed to identify all previously proposed IBM diagnostic criteria. These criteria were applied through medical records review to 200 patients diagnosed as having IBM and 171 patients diagnosed as having a muscle disease other than IBM by neuromuscular specialists at 2 institutions, and to a validating set of 66 additional patients with IBM from 2 other institutions. Machine learning techniques were used for unbiased construction of diagnostic criteria.

Results: Twenty-four previously proposed IBM diagnostic categories were identified. Twelve categories all performed with high (≥97%) specificity but varied substantially in their sensitivities (11%-84%). The best performing category was European Neuromuscular Centre 2013 probable (sensitivity of 84%). Specialized pathologic features and newly introduced strength criteria (comparative knee extension/hip flexion strength) performed poorly. Unbiased data-directed analysis of 20 features in 371 patients resulted in construction of higher-performing data-derived diagnostic criteria (90% sensitivity and 96% specificity).

Conclusions: Published expert consensus-derived IBM diagnostic categories have uniformly high specificity but wide-ranging sensitivities. High-performing IBM diagnostic category criteria can be developed directly from principled unbiased analysis of patient data.

Classification of evidence: This study provides Class II evidence that published expert consensus-derived IBM diagnostic categories accurately distinguish IBM from other muscle disease with high specificity but wide-ranging sensitivities.

© 2014 American Academy of Neurology.

Figures

Figure 1. Sensitivities and specificities of IBM…
Figure 1. Sensitivities and specificities of IBM categories and features
(A, B) IBM categories. (C, D) IBM features. CD = clinically defined; CK = creatine kinase; CPD = clinicopathologically defined; Def = definite; EM = electron microscopy; ENMC = European Neuromuscular Center; FF = finger flexion; HF = hip flexion; IBM = inclusion body myositis; IM = Institute of Myology; KE = knee extension; MRC = Medical Research Council; PD = pathologically defined; Poss = possible; Prob = probable; RV = rimmed vacuoles; SA = shoulder abduction; TF = tubulofilaments; WE = wrist extension; WF = wrist flexion.
Figure 2. Failure rates and reasons for…
Figure 2. Failure rates and reasons for IBM diagnostic criteria
(A) Failure rates for published IBM diagnostic categories according to most common criteria failed. (B) Failure rates of strength criteria. Ambiguity results from meeting strength criteria on one side of the body but failing on the other side. (C) Consistency of strength criteria failure rates at 4 institutions. The criterion of “finger flexion weakness” (FF 10 years for KE ≤ HF, KE

Figure 3. Hierarchical structure of 4 schemes…

Figure 3. Hierarchical structure of 4 schemes represented as Venn diagrams

(A) Griggs 1995 categories…

Figure 3. Hierarchical structure of 4 schemes represented as Venn diagrams
(A) Griggs 1995 categories are nonoverlapping and nonhierarchical. (B) ENMC 2000 categories probable and definite are a nested hierarchy: all patients who meet definite criteria also meet probable criteria, and no gaps are present if a patient with probable gains additional features. (C) MRC 2010 categories are a hybrid between nested hierarchy (all CD patients meet Poss criteria) and nonoverlapping nonhierarchical (no PD patients meet CD or Poss criteria). This scheme contains a gap (both CD and Poss patients can gain an inclusion body myositis feature, such as tubulofilaments, resulting in loss of CD or Poss status, but yet not graduate to PD). (D) ENMC 2013 criteria are a hybrid between nested hierarchy (all CD patients meet Prob criteria) and an overlapping nonhierarchical category (CPD patients can also meet Prob or CD criteria, or they can fail to meet either Prob or CD criteria). CD = clinically defined; CPD = clinicopathologically defined; Def = definite; ENMC = European Neuromuscular Center; MRC = Medical Research Council; PD = pathologically defined; Poss = possible; Prob = probable.
Figure 3. Hierarchical structure of 4 schemes…
Figure 3. Hierarchical structure of 4 schemes represented as Venn diagrams
(A) Griggs 1995 categories are nonoverlapping and nonhierarchical. (B) ENMC 2000 categories probable and definite are a nested hierarchy: all patients who meet definite criteria also meet probable criteria, and no gaps are present if a patient with probable gains additional features. (C) MRC 2010 categories are a hybrid between nested hierarchy (all CD patients meet Poss criteria) and nonoverlapping nonhierarchical (no PD patients meet CD or Poss criteria). This scheme contains a gap (both CD and Poss patients can gain an inclusion body myositis feature, such as tubulofilaments, resulting in loss of CD or Poss status, but yet not graduate to PD). (D) ENMC 2013 criteria are a hybrid between nested hierarchy (all CD patients meet Prob criteria) and an overlapping nonhierarchical category (CPD patients can also meet Prob or CD criteria, or they can fail to meet either Prob or CD criteria). CD = clinically defined; CPD = clinicopathologically defined; Def = definite; ENMC = European Neuromuscular Center; MRC = Medical Research Council; PD = pathologically defined; Poss = possible; Prob = probable.

Source: PubMed

3
Prenumerera