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Objective <p>Inflammation is implicated in many chronic diseases, but its role in driving multiple long-term conditions (MLTCs) remains unclear. The InflAIM programme aims to explore this potential link. Existing MLTC codelists are valuable but have not been designed for inflammation-focused research and often lack harmonisation across coding systems. This work aimed to develop a transparent, co-produced MLTC framework with harmonised codelists for epidemiological research, focusing on inflammatory conditions within the InflAIM programme.</p> Results <p>Using a systematic, co-produced approach, we combined literature review, clinical consensus, and patient input. From 8 sources, 363 candidate conditions were identified, refined to 60 validated MLTCs. Patients informed terminology and diagnostic experiences. Codelists were drawn from CALIBER (43), HDR UK Phenotype Library (4), MULTIPLY (8), with 7 developed de novo. Harmonisation covered Read v2, SNOMED CT, and Medcodeids. Quality assurance excluded 16.5% of codes and resolved 92 overlaps.We produced harmonised codelists for 60 MLTCs, comprising 7,426 validated MedCodeids. Clinical consensus identified 17 conditions with significant inflammatory components. Additional lists were developed for autoimmune and infectious diseases to support inflammation-focused analyses. This framework extends existing resources to meet the needs of inflammation-focused research, offering a transparent, harmonised, and patient-informed foundation for the InflAIM programme.</p>

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Harmonising definitions of multiple long term conditions for inflammation research: a co-production approach

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月13日

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  • Daniel Asfaw,
  • Charlotte Davies,
  • Elena Kulinskaya,
  • Tahmina Zebin,
  • Min Hane Aung,
  • Christopher Fox,
  • Benedict Alan Harries Jones,
  • Jasmyn Gooding,
  • John Ford,
  • Alexander J. MacGregor

摘要

Objective

Inflammation is implicated in many chronic diseases, but its role in driving multiple long-term conditions (MLTCs) remains unclear. The InflAIM programme aims to explore this potential link. Existing MLTC codelists are valuable but have not been designed for inflammation-focused research and often lack harmonisation across coding systems. This work aimed to develop a transparent, co-produced MLTC framework with harmonised codelists for epidemiological research, focusing on inflammatory conditions within the InflAIM programme.

Results

Using a systematic, co-produced approach, we combined literature review, clinical consensus, and patient input. From 8 sources, 363 candidate conditions were identified, refined to 60 validated MLTCs. Patients informed terminology and diagnostic experiences. Codelists were drawn from CALIBER (43), HDR UK Phenotype Library (4), MULTIPLY (8), with 7 developed de novo. Harmonisation covered Read v2, SNOMED CT, and Medcodeids. Quality assurance excluded 16.5% of codes and resolved 92 overlaps.We produced harmonised codelists for 60 MLTCs, comprising 7,426 validated MedCodeids. Clinical consensus identified 17 conditions with significant inflammatory components. Additional lists were developed for autoimmune and infectious diseases to support inflammation-focused analyses. This framework extends existing resources to meet the needs of inflammation-focused research, offering a transparent, harmonised, and patient-informed foundation for the InflAIM programme.