Department of Pathology, All India Institute of Medical Sciences (AIIMS), New Delhi, 110029, India.
Department of Pediatric Surgery, All India Institute of Medical Sciences, New Delhi, India.
Endocr Pathol. 2023 Jun;34(2):213-223. doi: 10.1007/s12022-023-09767-z. Epub 2023 May 9.
Adrenocortical neoplasms are rare in childhood. Their histopathological categorization into benign and malignant is often challenging, impacting further management. While the AFIP/Wieneke scoring system is widely used for the prognostic classification of these tumors, it has limitations. Few other tumor scoring systems have evolved over the past few years. These have been validated in adults but not yet in pediatric patients. We evaluated a cohort of pediatric adrenocortical neoplasms to assess the applicability of AFIP/Wieneke criteria and the recently introduced Helsinki score and reticulin algorithm in predicting clinical outcomes. A tumor was considered 'clinically aggressive' in the presence of any of the following: metastases, recurrence, progressive disease, or death due to disease. Cases without any such event were considered 'clinically good'. Event-free survival time was the duration from the date of clinical presentation to any post-operative adverse event. For overall survival analysis, the endpoint was either the last follow-up or death due to disease.Using ROC curve analysis, the obtained cut-off Helsinki score of 24 could stratify the cases into two prognostically relevant groups. Survival analysis showed significant differences in the event-free and overall survival of these two groups of patients, validating the proposed cut-off. None of the three histopathological scoring systems could predict an unfavorable outcome with 100% accuracy. All showed a sensitivity of ≥ 80%, with the reticulin algorithm achieving 100% sensitivity. The specificity and accuracy of the AFIP/Wieneke criteria were the lowest (62.5% and 73.08%, respectively). While the Helsinki score (at the cut-off score of 24) and the reticulin algorithm had similar accuracy rates (80.77%, and 80%, respectively), the specificity of the former was higher (81.25%) than the latter (68.75%). A separate analysis revealed that the Ki-67 index at a cut-off of 18% had a sensitivity of 80% and a specificity of 81.25% for predicting an unfavorable outcome.
儿童肾上腺皮质肿瘤较为罕见。这些肿瘤的组织病理学分类为良性和恶性往往具有挑战性,会影响进一步的治疗决策。虽然 AFIP/Wieneke 评分系统被广泛用于这些肿瘤的预后分类,但它存在局限性。在过去几年中,出现了一些其他肿瘤评分系统。这些系统已在成人中得到验证,但尚未在儿科患者中得到验证。我们评估了一组儿童肾上腺皮质肿瘤,以评估 AFIP/Wieneke 标准和最近引入的赫尔辛基评分和网状纤维算法在预测临床结局方面的适用性。如果存在以下任何一种情况,则认为肿瘤为“临床侵袭性”:转移、复发、进行性疾病或疾病导致的死亡。没有任何此类事件的病例被认为是“临床良好”。无事件生存时间是从临床表现到任何术后不良事件的时间。对于总生存分析,终点是最后一次随访或疾病导致的死亡。使用 ROC 曲线分析,获得的 24 分赫尔辛基评分可以将病例分为两个具有显著预后差异的组。生存分析显示这两组患者的无事件生存和总生存存在显著差异,验证了所提出的截断值。这三种组织病理学评分系统均无法 100%准确预测不良结局。所有评分系统的敏感性均≥80%,网状纤维算法的敏感性为 100%。AFIP/Wieneke 标准的特异性和准确性最低(分别为 62.5%和 73.08%)。虽然赫尔辛基评分(在截断分数为 24 时)和网状纤维算法的准确性相似(分别为 80.77%和 80%),但前者的特异性(81.25%)高于后者(68.75%)。单独分析显示,Ki-67 指数在 18%的截断值时,预测不良结局的敏感性为 80%,特异性为 81.25%。