Rahbar Haider, Bhayani Sam, Stifelman Michael, Kaouk Jihad, Allaf Mohamad, Marshall Susan, Zargar Homayoun, Ball Mark W, Larson Jeffrey, Rogers Craig
Vattikuti Urology Institute, Henry Ford Hospital, Detroit, Michigan.
Division of Urologic Surgery, Washington University School of Medicine, Saint Louis, Missouri.
J Urol. 2014 Nov;192(5):1337-42. doi: 10.1016/j.juro.2014.06.028. Epub 2014 Jun 14.
We evaluated a published biopsy directed small renal mass management algorithm using a large cohort of patients who underwent robotic partial nephrectomy for tumors 4 cm or smaller.
A simplified algorithm of biopsy directed small renal mass management previously reported using risk stratified biopsies was applied to 1,175 robotic partial nephrectomy cases from 5 academic centers. A theoretical assumption was made of perfect biopsies that were feasible for all patients and had 100% concordance to final pathology. Pathology risk groups were benign, favorable, unfavorable and intermediate. The algorithm assigned favorable or intermediate tumors smaller than 2 cm to active surveillance and unfavorable or intermediate 2 to 4 cm tumors to treatment. Higher surgical risk patients were defined as ASA® 3 or greater and age 70 years or older.
Patients were assigned to the pathology risk groups of benign (23%), favorable (13%), intermediate (51%) and unfavorable (12%). Patients were also assigned to the management groups of benign pathology (275, 23%), active surveillance (336, 29%) and treatment (564, 48%). Most of the 611 (52%) patients in the benign or active surveillance groups were low surgical risk and had safe treatment (2.6% high grade complications). A biopsy may not have been feasible or accurate in some tumors that were anterior (378, 32%), hilar (93, 7.9%) or less than 2 cm (379, 32%). Of 129 (11%) high surgical risk patients the biopsy algorithm assigned 70 (54%) to benign or active surveillance groups.
The theoretical application of a biopsy driven, risk stratified small renal mass management algorithm to a large robotic partial nephrectomy database suggests that about half of the patients might have avoided surgery. Despite the obvious limitations of a theoretical assumption of all patients receiving a perfect biopsy, the data support the emerging role of renal mass biopsies to guide management, particularly in high surgical risk patients.
我们使用一大群接受机器人辅助肾部分切除术治疗直径4厘米及以下肿瘤的患者，对已发表的活检导向性小肾肿块管理算法进行了评估。
将先前报道的使用风险分层活检的简化活检导向性小肾肿块管理算法应用于来自5个学术中心的1175例机器人辅助肾部分切除术病例。做出了一个理论假设，即完美活检对所有患者都是可行的，并且与最终病理结果的一致性为100%。病理风险组分为良性、有利、不利和中间型。该算法将直径小于2厘米的有利或中间型肿瘤分配至主动监测，将直径2至4厘米的不利或中间型肿瘤分配至治疗。手术风险较高的患者定义为美国麻醉医师协会（ASA）分级为3级或更高且年龄在70岁及以上。
患者被分配到良性（23%）、有利（13%）、中间型（51%）和不利（12%）的病理风险组。患者也被分配到良性病理管理组（275例，23%）、主动监测组（336例，29%）和治疗组（564例，48%）。良性或主动监测组的611例（52%）患者中，大多数手术风险较低且治疗安全（高级别并发症发生率为2.6%）。对于一些位于前方（378例，32%）、肾门处（93例，7.9%）或直径小于2厘米（379例，32%）的肿瘤，活检可能不可行或不准确。在129例（11%）手术风险较高的患者中，活检算法将70例（54%）分配至良性或主动监测组。
将活检驱动、风险分层的小肾肿块管理算法理论应用于一个大型机器人辅助肾部分切除术数据库表明，约一半的患者可能避免了手术。尽管所有患者都接受完美活检这一理论假设存在明显局限性，但数据支持肾肿块活检在指导管理方面日益重要的作用，尤其是在手术风险较高的患者中。
