Background and Objective:Insulinoma-associated protein 1 (INSM1) is a novel immunohistochemical marker with potential utility in identifying neuroendocrine differentiation in lung cancer. Unlike conventional neuroendocrine (NE) markers, INSM1 can potentially serve as a standalone diagnostic biomarker. This study presents the first meta-analysis assessing the diagnostic accuracy of using INSM1 to distinguish LCNEC and SCLC from other lung cancer subtypes, addressing the variability across individual studies.Methods:A systematic review and meta-analysis were conducted to comprehensively evaluate the diagnostic performance of INSM1 in the pathological classification of lung cancer. The online databases PubMed, Web of Science, and Embase were systematically searched for data collection. Studies reporting the sensitivity and specificity of INSM1 in diagnosing LCNEC and SCLC were included. Pooled estimates were calculated using two models: the NSCLC model, which distinguishes LCNEC from other non-small cell lung cancers (NSCLCs), and the lung cancer model, which differentiates both LCNEC and SCLC from non-neuroendocrine (non-NE) lung cancer.Results:Fourteen studies comprising 3,218 specimens were included in this systematic review and meta-analysis. In the NSCLC model, INSM1 demonstrated a pooled sensitivity of 0.67 (95% CI: 0.61–0.73) and specificity of 0.97 (95% CI: 0.96–0.98), with an area under the curve (AUC) of 0.943. In the lung cancer model, the pooled sensitivity and specificity were 0.86 (95% CI: 0.84–0.88) and 0.97 (95% CI: 0.96–0.98), respectively, with an AUC of 0.974.Conclusions:INSM1 demonstrated excellent diagnostic accuracy and consistently high specificity for pulmonary neuroendocrine carcinomas, supporting its utility as a reliable standalone immunohistochemical marker with the potential to replace conventional NE markers in the pathological diagnosis of LCNEC and SCLC.
背景与目的：胰岛素瘤相关蛋白1（INSM1）是一种新型免疫组化标志物，在识别肺癌神经内分泌分化方面具有潜在应用价值。与传统神经内分泌标志物不同，INSM1有望作为独立的诊断生物标志物。本研究首次通过荟萃分析评估INSM1在区分肺大细胞神经内分泌癌和小细胞肺癌与其他肺癌亚型中的诊断准确性，以解决各独立研究间的异质性问题。 方法：通过系统综述与荟萃分析全面评估INSM1在肺癌病理分型中的诊断效能。系统检索PubMed、Web of Science和Embase数据库进行数据收集。纳入报告INSM1诊断LCNEC和SCLC敏感度与特异度的研究。采用两种模型计算汇总估计值：非小细胞肺癌模型（区分LCNEC与其他非小细胞肺癌）和肺癌模型（区分LCNEC/SCLC与非神经内分泌肺癌）。 结果：本系统综述与荟萃分析共纳入14项研究，涵盖3,218份标本。在非小细胞肺癌模型中，INSM1的汇总敏感度为0.67（95% CI：0.61–0.73），特异度为0.97（95% CI：0.96–0.98），曲线下面积为0.943。在肺癌模型中，汇总敏感度与特异度分别为0.86（95% CI：0.84–0.88）和0.97（95% CI：0.96–0.98），曲线下面积达0.974。 结论：INSM1对肺神经内分泌癌展现出优异的诊断准确性和持续的高特异度，支持其作为可靠的独立免疫组化标志物，有望在LCNEC和SCLC的病理诊断中替代传统神经内分泌标志物。
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