Mapping patient journey in inflammatory bowel disease in Brazil: a cross-sectional descriptive study based on an online survey

  1. Marta Brenner Machado
  2. Flavio Steinwurz
  3. Cyrla Zaltman
  4. Patrícia Mendes Santos Quintiliano
  5. Manuela Mendes Moreira de Andrade Melo
  6. Silvana Paiva Orlandi
  7. Valéria Abrahão Schilling Rosenfeld

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  1. PREreview

    This Zenodo record is a permanently preserved version of a Structured PREreview. You can view the complete PREreview at https://prereview.org/reviews/15714857.

    Does the introduction explain the objective of the research presented in the preprint? Yes
    Are the methods well-suited for this research? Somewhat appropriate The methods are somewhat appropriate—they follow best practices in survey design, ethics, and descriptive analysis but have notable limitations in sampling, generalizability, and analytical depth. While the study provides valuable insights into the Brazilian IBD patient journey, the findings should be interpreted with caution due to potential biases. Recommendation for Improvement: Future studies should use stratified random sampling to better represent diverse socioeconomic groups. Incorporate clinical validation (e.g., linking survey data to medical records). Apply multivariate analyses to explore associations between delays in diagnosis and outcomes.
    Are the conclusions supported by the data? Somewhat supported The conclusions are mostly reasonable given the data but could be stronger with: Stratified analysis (e.g., comparing public vs. private healthcare outcomes). Inferential statistics to test hypotheses (e.g., "Does delayed diagnosis increase surgery risk?"). Updated data reflecting post-2020 treatment access changes. Thus, while the conclusions are plausible and data-informed, they stop short of being "highly supported" due to methodological gaps and overgeneralizations.
    Are the data presentations, including visualizations, well-suited to represent the data? Somewhat appropriate and clear Limitations Figure 1: Missing Context The charts lack confidence intervals or statistical significance markers (e.g., to compare delays between CD/UC). No stratification by healthcare system (SUS vs. private), which is a major discussion point in the text. Tables: Overwhelming Detail Table II (drug treatments) is dense and could benefit from highlighting key comparisons (e.g., biologics access disparity between CD/UC). Table III (quality of life) uses vague Likert-scale labels (e.g., "2-4 moderately disagree"), which could be simplified or visualized as a bar chart. Missing Visualizations for Key Findings No graphs for: The 20.3% with >3-year diagnostic delays (a critical result). Geographic disparities (58% of patients were from Southeast Brazil). Public vs. private healthcare comparisons (only 28.5% used SUS). Accessibility Gaps Color reliance: If printed in grayscale, Figure 1's segments might blend. No alternative text descriptions for visualizations (important for accessibility). Suggested Improvements Add a map of Brazil to show regional participation disparities. Include side-by-side bar charts for SUS vs. private healthcare outcomes. Simplify Likert-scale data in Table III with stacked bars or a heatmap. Use annotations in figures to emphasize key takeaways (e.g., "33.9% had ≥5 ER visits").
    How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research? Somewhat clearly Limitations Overgeneralization Without Nuance The discussion doesn't fully explore why delays occur (e.g., primary care barriers, cultural factors) or how to address them beyond broad policy recommendations. Missed Opportunities for Next Steps While the need for improved access is mentioned, specific proposals (e.g., telehealth for rural patients, SUS reforms) are lacking. No mention of patient education initiatives to reduce self-guided dietary changes (reported by 82.4%). Weaknesses in Data Limitations The private-healthcare skew (61.9% of sample) is noted but not deeply analyzed. For example: How might public-system patients' journeys differ? Repetitive Conclusions The takeaway that "IBD impacts quality of life" is reiterated without advancing new insights (e.g., actionable strategies to mitigate this). Suggested Improvements Add a "Recommendations" subsection with concrete steps (e.g., "Expand SUS coverage for biologics," "Integrate nutritionists into IBD clinics"). Discuss regional disparities (58% Southeast participation) and their implications. Propose future research (e.g., longitudinal studies on delays/surgery risk, qualitative work on patient experiences in public vs. private systems).
    Is the preprint likely to advance academic knowledge? Somewhat likely Limitations in Advancing Knowledge Methodological Constraints Convenience sampling bias (overrepresentation of affluent, urban patients) limits generalizability to Brazil's diverse population. Self-reported data lacks clinical validation (e.g., no linkage to medical records). Descriptive, Not Explanatory Identifies patterns (e.g., delays, treatment disparities) but does not statistically test root causes (e.g., socioeconomic predictors of delays). Dated Data (2017 Collection) Brazil's healthcare landscape has evolved (e.g., SUS biologics approval for UC in 2020), reducing relevance to current practice. Potential for Impact Clinical/Policy: Could inform Brazilian healthcare reforms (e.g., reducing diagnostic delays, expanding multidisciplinary care). Research: Sets a foundation for follow-up studies (e.g., longitudinal analyses, qualitative work on patient experiences).
    Would it benefit from language editing? Yes Issues Needing Improvement Grammar/Syntax Errors Example: "This makes our sample susceptible to selection bias, since participation was voluntary and non-probabilistic." → "This introduces selection bias, as participation was voluntary and non-random." Awkward Phrasing Example: "The drug treatment of Inflammatory Bowel Disease (IBD) often involves the use of several classes of drugs..." → "IBD treatment typically involves multiple drug classes..." Redundancy Example: "The results of this study are important because, according to the scientific literature..." → "This study's findings are significant because prior research shows..." Inconsistent Terminology Alternates between "multidisciplinary team" and "multidisciplinary care" without standardization. Overly Complex Sentences Example: "The difficulty in accessing biological therapies can be explained, in part, by the lack of reimbursement for this class of drugs in the SUS for UC, which mainly impacts patients without private health insurance." → "Limited SUS reimbursement for biologics in UC partly explains access barriers, especially for uninsured patients." Impact on Clarity While the text is generally understandable, these issues: Slow readability for non-native English speakers. Reduce precision in key arguments (e.g., policy recommendations). Suggested Edits Concise rewrites (e.g., avoid passive voice: "It was observed that..." → "We observed..."). Consistent terms (e.g., stick to "multidisciplinary care" throughout). Grammar polish (e.g., subject-verb agreement, article usage).
    Would you recommend this preprint to others? Yes, but it needs to be improved Areas Needing Improvement Methodological Limitations – Convenience sampling bias (overrepresents wealthier patients) and self-reported data weaken generalizability. Dated Data (2017) – Brazil's healthcare policies (e.g., biologics in SUS) have evolved, reducing current relevance. Language & Clarity – Requires editing for grammar, conciseness, and readability (as noted earlier). Lack of Advanced Analysis – Descriptive stats only; no regression/causal modeling to explore predictors of delays or outcomes. Recommended Audience Researchers studying IBD in LMICs (useful baseline data). Brazilian policymakers (evidence for healthcare reforms). Clinicians (insights into patient experiences).
    Is it ready for attention from an editor, publisher or broader audience? Yes, after minor changes Required Minor Improvements Language Edits – Grammar, conciseness, and terminology consistency (as noted earlier) to enhance readability. Updated Context – A brief discussion on how post-2017 changes (e.g., SUS biologics approval for UC) might affect the interpretation of results. Limitations Section Expansion – Explicitly address: Sampling bias (overrepresentation of private healthcare users). Self-reporting limitations (potential recall bias). Visual Clarity – Minor tweaks to tables/figures (e.g., highlighting key comparisons in Table II).

    Competing interests

    The author declares that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The author declares that they used generative AI to come up with new ideas for their review.

  2. Version published to 10.1590/scielopreprints.11878 on SciELO Preprints