Review for 10.1186/s12876-025-04042-3 (2025)

Title: Global, Regional, and National Burden of Inflammatory Bowel Disease in persons Aged
60-89 years from 1992 to 2021
Version: 1 Date: 30 Mar 2025
Reviewer's report:
This study provides a comprehensive analysis of the global, regional, and national burden of IBD
among older adults (60–89 years) using data from the GBD 2021 database. Key findings include
rising age-standardized incidence rates (ASIR: +0.34% AAPC) alongside declining prevalence
(ASPR: -0.04% AAPC), mortality (ASMR: -0.60% AAPC), and disability-adjusted life years
(ASDR: -0.49% AAPC) from 1992 to 2021. Significant disparities were observed across SDI
levels (e.g., High SDI regions had the highest ASIR/ASPR, while Middle SDI regions showed
the fastest ASIR growth). Forecasts predict continued incidence increases but further declines in
mortality and DALYs by 2030. The study underscores the need for region-specific public health
strategies, particularly in low-resource settings. While methodologically rigorous, the analysis
has limitations, including insufficient exploration of IBD subtypes, treatment heterogeneity, and
environmental determinants.
Major Weaknesses
1. Lack of IBD Subtype Differentiation:
- Fails to distinguish between Crohn’s disease and ulcerative colitis, which have distinct risk
factors, progression, and mortality profiles. This limits clinical relevance and masks subtype-
specific trends.
2. Inadequate Subgroup Analysis of Older Adults:
- Treats the 60–89 age group as homogeneous. Subgroup analysis (e.g., 60–69 vs. 80–89) could
reveal age-specific trends in disease severity, comorbidities, or treatment responses.
3. Underestimation in Low-Resource Settings:
- Relies on GBD data, which may underrepresent regions with poor diagnostic infrastructure.
Underdiagnosis in Low SDI regions likely skews incidence/prevalence estimates downward.
4. Omission of Comorbidities and Treatment Data:
- Does not adjust for comorbidities (e.g., diabetes, cardiovascular disease) common in older
adults, which may confound mortality/DALY trends.
- Limited discussion of treatment access (e.g., biologics, surgery rates) and its role in declining
mortality.
Minor Weaknesses
1. Inconsistent Terminology:
- Alternates between "older persons" and "elderly" without standardization.
2. SDI aggregates economic, educational, and fertility metrics but does not capture healthcare
system-specific factors (e.g., insurance coverage, specialist availability).
3. Borderline Statistical Results:
- The Americas’ ASIR (AAPC 0.27, p=0.057) is dismissed as non-significant without
contextualizing potential clinical relevance.
Limitations Not Addressed by Authors
1. Environmental and Behavioral Risk Factors:
- Fails to incorporate data on dietary patterns (e.g., processed food consumption), smoking rates,
or air pollution, which are implicated in IBD pathogenesis and regional disparities.
2. Cultural and Healthcare System Nuances:
- Does not explore cultural stigma, health-seeking behaviors, or traditional medicine use in Low
SDI regions, which may delay diagnosis and treatment.
3. Modeling Assumptions in Forecasting:
- Nordpred projections assume linear trends and do not account for disruptive events (e.g.,
COVID-19, climate change) post-2021, potentially overestimating 2030 accuracy.
4. Survivorship Bias:
- Older adults included in prevalence estimates may represent "healthier" survivors, skewing
ASPR declines upward.
5. Gender-Specific Analysis Gaps:
- While gender differences in AAPC are noted, the study does not explore biological (e.g.,
hormonal) or sociocultural (e.g., caregiving roles) drivers of these trends.
Recommendations for Revision
1. Subtype and Subgroup Analysis:
- Stratify results by IBD subtype (Crohn’s vs. ulcerative colitis) and age subgroups (e.g., 60–
69, 70–79, 80–89).
2. Integrate Comorbidity and Treatment Data :
- Adjust analyses for common comorbidities and include treatment accessibility metrics (e.g.,
biologics usage rates by region).
3. Expand on Environmental Determinants:
- Incorporate datasets on diet, pollution, and smoking to strengthen mechanistic explanations
for regional trends.
4. Address Underdiagnosis
- Model correction factors for underreporting in Low SDI regions using sensitivity analyses.
5. Clarify Forecasting Limitations:
- Acknowledge potential disruptions (e.g., pandemics, policy shifts) that could alter 2030
projections.