Real-world application of the international myositis assessment and clinical studies group guidelines on cancer risk stratification
Year: 2026
Type: article
Study design: Observational Study
Abstract: OBJECTIVES: The 2023 International Myositis Assessment and Clinical Studies Group (IMACS) guidelines introduced a standardized risk-stratification model for cancer screening in idiopathic inflammatory myopathies (IIM). However, real-world data on their application remain limited. This study aimed to evaluate the effectiveness of IMACS-based risk stratification in predicting malignancy and assess adherence to cancer screening recommendations in a multicentric Italian IIM cohort. METHODS: We conducted a multicentre retrospective study including 411 IIM patients from five Italian rheumatology centres, classified into IMACS-defined standard, intermediate and high-risk groups. Cancer occurrence within three years of IIM diagnosis was assessed. Screening practices prior to the implementation of IMACS guidelines were compared with their recommendations. Logistic regression analysis was used to evaluate the predictive value of IMACS stratification. RESULTS: Among 411 patients, 180 (43.8%) were classified as high-risk, 156 (37.7%) as intermediate-risk and 75 (18.2%) as standard-risk. Cancer was diagnosed in 9.2% of patients within three years of IIM onset, with high-risk patients significantly more likely to develop malignancy (OR = 4.05, P = 0.026). Anti-TIF1γ (OR = 12.3, P < 0.001) and anti-SAE1 (OR = 11.9, P = 0.012) were independent predictors of cancer. Screening adherence varied, with underutilization of enhanced screening in intermediate-risk patients and a decline in screening over time. CONCLUSION: The IMACS stratification model effectively predicts cancer risk in IIM. However, real-world screening practices show inconsistencies, particularly in intermediate-risk patients. These findings support the need for optimized, risk-adapted malignancy surveillance in IIM and refinement of current guidelines based on real-world data.
Source: Lara D. Veeken
Authors: Maria Rosa Pellico, Cristina Bochicchio, Claudia Iannone, Silvia Cavalli, Ilaria Magi, Veronica Batani, Antonio Tonutti, Silvia Grazzini, Silvia Della Pina, Alessia Gatti, Manuel Sette, Antonina Minniti, Maria De Santis, Angela Ceribelli, Edoardo Conticini, Ilaria Cavazzana, Corrado Campochiaro, Giacomo De Luca, Roberto Caporali, Nicoletta Del Papa
Institutions: University of Milan, University of Modena and Reggio Emilia, Vita-Salute San Raffaele University, IRCCS Ospedale San Raffaele, Humanitas University, IRCCS Humanitas Research Hospital, University of Siena, Azienda Socio Sanitaria Territoriale degli Spedali Civili di Brescia, ERN ReCONNET, University of Brescia
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7149987566