Addressing the gaps in biologic therapy utilization trends in IBD from Saudi Arabia
Bibliographic record
Abstract
Dear Editor, We read with great interest your narrative review on biologic therapy utilization in inflammatory bowel disease (IBD) in Saudi Arabia.[1] The paper offers a timely and well-balanced overview of how IBD care is evolving in the Kingdom, where the rise in disease incidence parallels the growing use of advanced biologic and small-molecule therapies. The review does an excellent job of summarizing available data and bringing attention to the urgent need for stronger real-world evidence and cost-effectiveness research to support local decision-making. A few points, however, deserve further discussion. The review highlights the continued predominance of infliximab and adalimumab, with infliximab showing better treatment durability, particularly in Crohn’s disease.[1] This observation is consistent with regional data. Alharbi and colleagues, for example, found infliximab to have higher persistence rates than adalimumab in Saudi IBD patients, while noting that limited access to therapeutic drug monitoring (TDM) remains a major barrier to optimizing treatment.[2] Broader adoption of TDM across Saudi centers could help reduce both primary non-response and secondary loss of response—problems that remain particularly frequent among ulcerative colitis patients. Shifting from empiric dosing to TDM-guided adjustment would also move local practice closer to precision medicine standards seen in other parts of the world. Equally important is the growing use of newer biologics such as ustekinumab and vedolizumab in patients who fail anti-tumor necrosis factor (TNF) therapy, including children and adolescents. Local studies have shown encouraging outcomes regarding both safety and clinical response in these settings.[3,4] Even so, most of these reports come from small retrospective series with variable outcome measures, which limits how broadly the results can be applied. As you suggested, developing a national IBD registry would be a major step forward. A centralized database capturing disease phenotype, prior biologic exposure, biomarkers, endoscopic findings, adverse events, and patient-reported outcomes, would provide the type of real-world data needed to guide both clinical care and policy decisions. The economic side of biologic therapy also warrants close attention. Reported annual treatment costs in Saudi Arabia range from about US $5,500 to US $18,400, compared with less than US $600 for non-biologic regimens.[5] This gap remains substantial even as biosimilars gain traction. Recent modeling work by Mosli and colleagues[6] evaluated the financial impact of introducing upadacitinib and risankizumab for moderate-to-severe IBD. After accounting for real-world dose adjustments, they estimated that total annual costs rose by roughly 6.7% with upadacitinib and fell by 0.35% with risankizumab, while the total number of treated patients increased by 22%. These findings suggest that, despite improvements in efficacy and convenience, newer agents still impose a considerable financial burden on national healthcare budgets. Systematic promotion of biosimilar use, combined with TDM-based optimization and clear pharmacoeconomic frameworks, will be essential for maintaining the sustainability of IBD care. Your mention of dual biologic therapy and small-molecule combinations is also worth emphasizing. Early reports suggest these strategies may help in otherwise refractory disease, but regional safety data are limited. El-Atrebi and colleagues[7] recently highlighted both the potential benefits and the need for strong pharmacovigilance before widespread adoption. Coordinated multicenter studies in Saudi Arabia could help determine where such combinations fit best in practice. In summary, your review provides an important foundation for understanding current biologic utilization patterns in Saudi Arabia. Building on your work, three issues seem particularly critical for the next phase of IBD care: wider implementation of TDM-guided dosing to extend biologic durability, rapid development of a national registry to generate standardized outcome data, and structured incorporation of biosimilar and cost-effectiveness policies to ensure sustainable access. Taken together, these initiatives would help translate the recent therapeutic advances in IBD into durable, equitable, and value-based care for patients across the Kingdom. Sincerely, Zaki Alhashimalsayed Financial Support and Sponsorship None. Conflict of interest The authors declare no conflicts of interest.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".