Carroll Nikki M, Ritzwoller Debra P, Banegas Matthew P, O'Keeffe-Rosetti Maureen, Cronin Angel M, Uno Hajime, Hornbrook Mark C, Hassett Michael J
Kaiser Permanente Colorado, Denver, CO.
Kaiser Permanente Center for Health Research, Portland, OR.
JCO Clin Cancer Inform. 2019 Mar;3:1-9. doi: 10.1200/CCI.18.00113.
We previously developed and validated informatic algorithms that used International Classification of Diseases 9th revision (ICD9)-based diagnostic and procedure codes to detect the presence and timing of cancer recurrence (the RECUR Algorithms). In 2015, ICD10 replaced ICD9 as the worldwide coding standard. To understand the impact of this transition, we evaluated the performance of the RECUR Algorithms after incorporating ICD10 codes.
Using publicly available translation tables along with clinician and other expertise, we updated the algorithms to include ICD10 codes as additional input variables. We evaluated the performance of the algorithms using gold standard recurrence measures associated with a contemporary cohort of patients with stage I to III breast, colorectal, and lung (excluding IIIB) cancer and derived performance measures, including the area under the receiver operating curve, average absolute prediction error, and correct classification rate. These values were compared with the performance measures derived from the validation of the original algorithms.
A total of 659 colorectal, 280 lung, and 2,053 breast cancer cases were identified. Area under the receiver operating curve derived from the updated algorithms was 89.0% (95% CI, 82.3% to 95.7%), 88.9% (95% CI, 79.3% to 98.2%), and 80.5% (95% CI, 72.8% to 88.2%) for the colorectal, lung, and breast cancer algorithms, respectively. Average absolute prediction errors for recurrence timing were 2.7 (SE, 11.3%), 2.4 (SE, 10.4%), and 5.6 months (SE, 21.8%), respectively, and timing estimates were within 6 months of actual recurrence for more than 80% of colorectal, more than 90% of lung, and more than 50% of breast cancer cases using the updated algorithm.
Performance measures derived from the updated and original algorithms had overlapping confidence intervals, suggesting that the ICD9 to ICD10 transition did not affect the RECUR Algorithm performance.
我们之前开发并验证了信息学算法，该算法使用基于国际疾病分类第九版（ICD9）的诊断和程序代码来检测癌症复发的存在和时间（RECUR算法）。2015年，ICD10取代ICD9成为全球编码标准。为了解这一转变的影响，我们在纳入ICD10代码后评估了RECUR算法的性能。
利用公开可用的翻译表以及临床医生和其他专业知识，我们更新了算法，将ICD10代码作为额外的输入变量。我们使用与I至III期乳腺癌、结直肠癌和肺癌（不包括IIIB期）患者的当代队列相关的金标准复发指标以及推导的性能指标来评估算法的性能，这些指标包括受试者操作特征曲线下面积、平均绝对预测误差和正确分类率。将这些值与原始算法验证得出的性能指标进行比较。
共识别出659例结直肠癌、280例肺癌和2053例乳腺癌病例。更新后的算法得出的受试者操作特征曲线下面积，结直肠癌算法为89.0%（95%CI，82.3%至95.7%），肺癌算法为88.9%（95%CI，79.3%至98.2%），乳腺癌算法为80.5%（95%CI，72.8%至88.2%）。复发时间的平均绝对预测误差分别为2.7个月（SE，11.3%）、2.4个月（SE，10.4%）和5.6个月（SE，21.8%），使用更新后的算法，超过80%的结直肠癌病例、超过90%的肺癌病例和超过50%的乳腺癌病例的时间估计在实际复发的6个月内。
更新后的算法和原始算法得出的性能指标具有重叠的置信区间，表明从ICD9到ICD10的转变并未影响RECUR算法的性能。
