Topic modeling and text mining are subsets of Natural Language Processing (NLP) with relevance for conducting meta-analysis (MA) and systematic review (SR). For evidence synthesis, the above NLP methods are conventionally used for topic-specific literature searches or extracting values from reports to automate essential phases of SR and MA. Instead, this work proposes a comparative topic modeling approach to analyze reports of contradictory results on the same general research question. Specifically, the objective is to identify topics exhibiting distinct associations with significant results for an outcome of interest by ranking them according to their proportional occurrence in (and consistency of distribution across) reports of significant effects. The proposed method was tested on broad-scope studies addressing whether supplemental nutritional compounds significantly benefit macular degeneration (MD). Four of these were further supported in terms of effectiveness upon conducting a follow-up literature search for validation (omega-3 fatty acids, copper, zeaxanthin, and nitrates). The two not supported by the follow-up literature search (niacin and molybdenum) also had scores in the lowest range under the proposed scoring system, suggesting that the proposed methods score for a given topic may be a viable proxy for its degree of association with the outcome of interest and can be helpful in the search for potentially causal relationships. These results underpin the proposed methods potential to add specificity in understanding effects from broad-scope reports, elucidate topics of interest for future research, and guide evidence synthesis in a systematic and scalable way. All of this is accomplished while yielding valuable insights into the prevention of MD.

翻译：主题建模和文本挖掘是自然语言处理（NLP）的子集，与元分析（MA）和系统评价（SR）的实施密切相关。在证据综合方面，上述NLP方法通常用于特定主题的文献检索或从报告中提取数值，以自动化SR和MA的关键阶段。相反，本研究提出了一种比较主题建模方法，用于分析针对同一研究问题得出矛盾结论的报告。具体而言，其目标是通过根据主题在显著效应报告中的出现比例（及跨报告分布一致性）进行排序，识别出与特定结局指标的显著结果呈现独特关联的主题。该方法的有效性通过对范围广泛的研究进行验证——这些研究探讨了补充性营养化合物是否对黄斑变性（MD）有显著益处。其中四种化合物（ω-3脂肪酸、铜、叶黄素和硝酸盐）在后续文献检索验证中被进一步支持其有效性。未获后续文献支持的两项（烟酸和钼）在本研究评分体系中亦处于最低分区间，表明所提方法对特定主题的评分可作为其与关注结局关联程度的可行替代指标，并有助于探寻潜在因果关系。这些结果支撑了该方法在以下方面的潜力：增强对广泛研究报告效应的特异性理解，阐明未来研究的关注主题，并以系统化、可扩展的方式指导证据综合。同时，该方法为MD的预防提供了宝贵见解。