*Section of Advanced Heart Failure and Transplantation, Division of Cardiology, University of Colorado Anschutz Medical Center, Aurora, CO †Department of Population Sciences, Henry Ford Hospital and Health System, Detroit, MI ‡Department of Epidemiology, Boston University School of Public Health, Boston, MA §Group Health Research Institute, Group Health Cooperative, Seattle, WA ∥Division of Research, Kaiser Permanente Northern California, Oakland, CA ¶Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School #Department of Medicine, Harvard Vanguard Medical Associates, Boston, MA **Center for Health Research-Southeast, Kaiser Permanente Georgia, Atlanta, GA ††Marshfield Clinic Research Foundation, Marshfield Clinic, Marshfield ‡‡Department of Hematology/Oncology, Weston, WI §§Institute for Health Research, Kaiser Permanente Colorado, Denver, CO.
Med Care. 2014 May;52(5):e30-8. doi: 10.1097/MLR.0b013e31825a8c22.
Cardiotoxicity is a known complication of certain breast cancer therapies, but rates come from clinical trials with design features that limit external validity. The ability to accurately identify cardiotoxicity from administrative data would enhance safety information.
To characterize the performance of clinical coding algorithms for identification of cardiac dysfunction in a cancer population.
We sampled 400 charts among 6460 women diagnosed with incident breast cancer, tumor size ≥ 2 cm or node positivity, treated within 8 US health care systems between 1999 and 2007. We abstracted medical records for clinical diagnoses of heart failure (HF) and cardiomyopathy (CM) or evidence of reduced left ventricular ejection fraction. We then assessed the performance of 3 different International Classification of Diseases, 9th Edition (ICD-9)-based algorithms.
The HF/CM coding algorithm designed a priori to balance performance characteristics provided a sensitivity of 62% (95% confidence interval, 40%-80%), specificity of 99% (range, 97% to 99%), positive predictive value (PPV) of 69% (range, 45% to 85%), and negative predictive value (NPV) of 98% (range, 96% to 99%). When applied only to incident HF/CM (ICD-9 codes and gold standard diagnosis both occurring after breast cancer diagnosis) in patients exposed to anthracycline and/or trastuzumab therapy, the PPV was 42% (range, 14% to 76%).
Claims-based algorithms have moderate sensitivity and high specificity for identifying HF/CM among patients with invasive breast cancer. As the prevalence of HF/CM among the breast cancer population is low, ICD-9 codes have high NPV but only moderate PPV. These findings suggest a significant degree of misclassification due to HF/CM overcoding versus incomplete clinical documentation of HF/CM in the medical record.
心脏毒性是某些乳腺癌治疗的已知并发症，但这些数据来自临床试验，其设计特征限制了外部有效性。能够从管理数据中准确识别心脏毒性将增强安全性信息。
描述用于识别癌症人群中心脏功能障碍的临床编码算法的性能。
我们在 1999 年至 2007 年间，从 6460 名患有浸润性乳腺癌、肿瘤大小≥2 厘米或淋巴结阳性、在 8 个美国医疗保健系统内接受治疗的女性中抽取了 400 份病历。我们从病历中提取心力衰竭（HF）和心肌病（CM）的临床诊断或左心室射血分数降低的证据。然后，我们评估了 3 种不同的基于国际疾病分类，第 9 版（ICD-9）的算法的性能。
预先设计的 HF/CM 编码算法在性能特征上达到了平衡，其敏感性为 62%（95%置信区间，40%-80%），特异性为 99%（范围，97%-99%），阳性预测值（PPV）为 69%（范围，45%-85%），阴性预测值（NPV）为 98%（范围，96%-99%）。当仅应用于接受蒽环类药物和/或曲妥珠单抗治疗且发生在乳腺癌诊断后的新发 HF/CM（ICD-9 代码和金标准诊断均发生在乳腺癌诊断之后）患者中时，PPV 为 42%（范围，14%-76%）。
基于索赔的算法对识别浸润性乳腺癌患者中的 HF/CM 具有中等敏感性和高特异性。由于 HF/CM 在乳腺癌人群中的患病率较低，因此 ICD-9 代码具有较高的 NPV，但仅有中等的 PPV。这些发现表明，由于 HF/CM 过度编码与医疗记录中 HF/CM 临床记录不完整，存在很大程度的误诊。
