NEJM：预测肺癌风险更准确的模型

来自Brock 大学的Martin C. Tammemagi和他的同事们通过收集80375个吸烟者的数据，根据（PLCO）癌症筛选试验开发出了一个肺癌风险预测模型。研究者们利用对照组获得的数据开发模型，干预组获得的数据用来验证模型。并把这个模型与全国肺癌筛查实验（NLST）制定的标准模型进行了比较。

研究人员发现受试者工作特征曲线面积为0.803时用来开发数据，而当面积为0.797时用于验证数据。与来自NLST的筛选标准相比，PLCO标准极大的提高了模型的敏感性（83%比71.1%），而且具有相似的特异性（62.9%比62.7%）。总之，Tammemagi表示：“PLCO模型与NLST标准模型相比，能更加准确预测6年肺癌风险而且在肺癌筛查中能更有效的识别。”


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Selection Criteria for Lung-Cancer Screening


BACKGROUND
The National Lung Screening Trial (NLST) used risk factors for lung cancer (e.g., ≥30 pack-years of smoking and <15 years since quitting) as selection criteria for lung-cancer screening. Use of an accurate model that incorporates additional risk factors to select persons for screening may identify more persons who have lung cancer or in whom lung cancer will develop.
METHODS
We modified the 2011 lung-cancer risk-prediction model from our Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial to ensure applicability to NLST data; risk was the probability of a diagnosis of lung cancer during the 6-year study period. We developed and validated the model (PLCOM2012) with data from the 80,375 persons in the PLCO control and intervention groups who had ever smoked. Discrimination (area under the receiver-operating-characteristic curve [AUC]) and calibration were assessed. In the validation data set, 14,144 of 37,332 persons (37.9%) met NLST criteria. For comparison, 14,144 highest-risk persons were considered positive (eligible for screening) according to PLCOM2012 criteria. We compared the accuracy of PLCOM2012 criteria with NLST criteria to detect lung cancer. Cox models were used to evaluate whether the reduction in mortality among 53,202 persons undergoing low-dose computed tomographic screening in the NLST differed according to risk.
RESULTS
The AUC was 0.803 in the development data set and 0.797 in the validation data set. As compared with NLST criteria, PLCOM2012 criteria had improved sensitivity (83.0% vs. 71.1%, P<0.001) and positive predictive value (4.0% vs. 3.4%, P=0.01), without loss of specificity (62.9% and. 62.7%, respectively; P=0.54); 41.3% fewer lung cancers were missed. The NLST screening effect did not vary according to PLCOM2012risk (P=0.61 for interaction).
CONCLUSIONS
The use of the PLCOM2012 model was more sensitive than the NLST criteria for lung-cancer detection.

来源：测序中国