Sazonova Olga, Manem Venkata, Béland Chloé, Hamel Marc-André, Lacasse Yves, Lévesque Marie-Hélène, Orain Michèle, Joubert David, Provencher Steeve, Simonyan David, Joubert Philippe
Institut Universitaire de Cardiologie et de Pneumologie de Québec (Québec Heart and Lung Institute) Research Center, Laval University, Québec, Canada.
Department of Medicine, Université Laval, Québec, Canada.
JTO Clin Res Rep. 2020 Jul 24;1(4):100078. doi: 10.1016/j.jtocrr.2020.100078. eCollection 2020 Nov.
Diffuse idiopathic pulmonary neuroendocrine hyperplasia (DIPNECH) is a rare condition that is likely underdiagnosed owing to the lack of established and validated diagnostic criteria. These clinical guidelines are empirical and created on the basis of a limited number of studies. This study was designed to validate the existing criteria and to identify new clinical parameters that can accurately diagnose DIPNECH.
Patients with DIPNECH were identified from a cohort that underwent surgical lung resection for pulmonary carcinoids. The study cohort included a total of 105 consecutive cases with neuroendocrine lesions. Initial diagnostic predictors of DIPNECH were selected from the literature. We employed univariate and multivariate models to evaluate the association of clinical, pathologic, radiologic variables with the likelihood of DIPNECH.
Univariate analysis identified age, sex, chronic obstructive pulmonary disease diagnosis, obstructive abnormalities, pulmonary nodules, mosaicism, absolute numbers of pulmonary neuroendocrine lesions (PNELs), and the number of tumorlets as significant DIPNECH predictors (for < 0.05). After adjustment for sampling variations, the ratio of the total number of PNELs to the number of bronchioles was found to be considerably higher in DIPNECH category. Multivariate analysis identified the total number of PNELs and multiple pulmonary nodules (>10) as independent predictors of DIPNECH. The performance of our criteria revealed an accuracy of 76% in detecting DIPNECH cases.
We proposed a set of diagnostic criteria for DIPNECH on the basis of an expert-panel approach integrating pathological features, radiology, and clinical data. Our findings will help identify DIPNECH patients, without a pathological confirmation of a neuroendocrine lesion. Before the implementation of these criteria in clinical practice, they require further validation in multi-institutional cohorts.
弥漫性特发性肺神经内分泌细胞增生症（DIPNECH）是一种罕见病症，由于缺乏既定且经过验证的诊断标准，其可能未得到充分诊断。这些临床指南是基于有限数量的研究经验性制定的。本研究旨在验证现有标准，并确定能够准确诊断DIPNECH的新临床参数。
从因肺类癌接受手术肺切除的队列中识别出DIPNECH患者。研究队列共纳入105例连续的神经内分泌病变病例。DIPNECH的初始诊断预测指标从文献中选取。我们采用单变量和多变量模型来评估临床、病理、放射学变量与DIPNECH可能性之间的关联。
单变量分析确定年龄、性别、慢性阻塞性肺疾病诊断、阻塞性异常、肺结节、马赛克征、肺神经内分泌病变（PNELs）的绝对数量以及微瘤数量为显著的DIPNECH预测指标（P<0.05）。在对抽样变异进行调整后，发现DIPNECH组中PNELs总数与细支气管数量的比值明显更高。多变量分析确定PNELs总数和多个肺结节（>10个）为DIPNECH的独立预测指标。我们标准的性能显示在检测DIPNECH病例方面的准确率为76%。
我们基于整合病理特征、放射学和临床数据的专家小组方法，提出了一套DIPNECH的诊断标准。我们的研究结果将有助于识别未经过神经内分泌病变病理确认的DIPNECH患者。在这些标准应用于临床实践之前，需要在多机构队列中进行进一步验证。
