Ultra-Rare Disease Health Technology Assessments in Brazil - Dataset and Data Dictionary

This dataset supports a retrospective observational study of all health technology assessment (HTA) reports for ultra-rare disease drugs issued by Brazil's National Commission for Health Technology Incorporation (Conitec) between 2011 and December 2025. The unit of analysis is the drug–indication pair; 63 reports covering 55 drugs across 36 ultra-rare diseases met eligibility criteria. Data were extracted in duplicate from publicly available Conitec reports using a standardized spreadsheet and data dictionary. Variables cover disease and technology characteristics, clinical evidence, economic evaluation, and appraisal process. The primary outcome was the final Conitec recommendation, classified as favorable, unfavorable, or reconsidered after public consultation. File 1 — conitec_2026 (source screening database) Complete panel of Conitec health technology assessment reports (N = 1,180) covering all technologies evaluated by Conitec, used as the source database from which ultra-rare disease drug reports were identified and screened for eligibility, as described in the Methods (Study design, eligibility criteria and data sources). File 2 — extraction_spreadsheet_DUR (extracted data) The analytic dataset extracted in duplicate from the 63 eligible Conitec reports, one row per drug–indication pair, covering all variables across the six domains described in the Methods (disease and technology characteristics, report characteristics, clinical evidence, economic evaluation, appraisal recommendation, and process characteristics). File 3 — dataset_DUR (data dictionary) Data dictionary defining each variable in the extraction spreadsheet: column letter, domain/category, variable name, description, possible values, coding criteria, and definition of missing-data codes (NA/NE) used during extraction. File 4 — analysis_script_DUR (statistical analysis code) R script (R version 4.6.0) used to reproduce all statistical analyses and figures reported in the manuscript, including normality testing, group comparisons, post-hoc pairwise comparisons, crude odds ratio calculations, and all publication figures.本数据集支持针对2011年至2025年12月由巴西国家健康技术纳入委员会（Conitec, National Commission for Health Technology Incorporation）发布的所有超罕见病药物健康技术评估（HTA, Health Technology Assessment）报告开展的回顾性观察研究。分析单位为药物-适应症配对；共有63份报告符合纳入标准，涵盖36种超罕见病的55种药物。数据通过标准化电子表格与数据字典，从公开可获取的Conitec报告中双人独立提取。变量涵盖疾病与技术特征、临床证据、经济学评价以及审评流程。主要结局为Conitec最终审评建议，分为有利、不利或经公众咨询后重新审议三类。 文件1 — conitec_2026（来源筛选数据库） 该文件包含Conitec评估过的所有技术对应的完整Conitec健康技术评估报告集（N=1180），作为源数据库，用于筛选并识别符合条件的超罕见病药物报告，具体方法详见研究方法部分（研究设计、纳入标准与数据来源）。 文件2 — extraction_spreadsheet_DUR（提取数据） 该分析数据集从63份符合纳入标准的Conitec报告中双人独立提取得到，每一行对应一个药物-适应症配对，涵盖研究方法部分所述六大领域的全部变量：疾病与技术特征、报告特征、临床证据、经济学评价、审评建议以及流程特征。 文件3 — dataset_DUR（数据字典） 该数据字典对提取电子表格中的每个变量进行定义，包括列标识、领域/类别、变量名称、变量描述、可能取值、编码标准以及提取过程中使用的缺失值编码（NA/NE）定义。 文件4 — analysis_script_DUR（统计分析代码） 该R脚本（R版本4.6.0）用于复现论文中报告的所有统计分析与图表，包括正态性检验、组间比较、事后两两比较、粗比值比计算以及所有可发表图表。