Gauger Paul G, Mullan Michelle H, Thompson Norman W, Doherty Gerard M, Matz Keith A, England Barry G
Division of Endocrine Surgery, Department of Surgery, University of Michigan Medical School, Ann Arbor, USA.
Arch Surg. 2004 Feb;139(2):164-9. doi: 10.1001/archsurg.139.2.164.
A nomogram based on regression analysis of intraoperative parathyroid hormone level decay discriminates single gland disease from multiglandular (MG) disease more accurately than the currently used 50% rule.
Retrospective case series.
Academic health center.
Two hundred thirty-five patients (222 patients with single gland disease and 13 patients with MG disease) who underwent parathyroidectomy.
Intraoperative parathyroid hormone level analysis at baseline, time 1 (about 5 minutes), and time 2 (about 10 minutes) after excision of the first gland.
The mean slope was calculated at time 1 and time 2 and analyzed using one-way analysis of variance and the Fisher least significance difference post hoc tests using data normalized to baseline intraoperative parathyroid hormone levels to compare patients with single gland disease with patients with MG disease. A regression-based nomogram was created to analyze individual kinetic decay data.
The mean (SEM) single gland disease slope was significantly steeper than the MG disease slope at both time 1 (-0.91 [0.02] vs -0.66 [0.05]; P<.01) and time 2 (-0.77 [0.01] vs -0.56 [0.05]; P<.01). When the standard threshold rule of a 50% decrease from baseline was used, only 23% of the patients with MG disease were correctly predicted by intraoperative parathyroid hormone values (77% false-positive result rate) at time 1. However, the nomogram correctly predicted 54% of the patients with MG disease at time 1 (46% false-positive result rate). At time 2, the standard threshold 50%-rule method correctly predicted 38% of the patients with MG disease (62% false-positive result rate), while the nomogram still correctly classified 54% of the patients with MG disease (46% false-positive result rate).
A regression-based nomogram incrementally improves prediction of MG disease compared with the standard 50%-rule method and accounts for variability in the exact timing of samples. Slope analysis suggests that the earliest time point best isolates the kinetics of the excised gland. The nomogram will need to be validated prospectively.
基于术中甲状旁腺激素水平衰减回归分析的列线图比目前使用的50%规则能更准确地区分单发性甲状旁腺疾病与多腺体疾病。
回顾性病例系列研究。
学术健康中心。
235例行甲状旁腺切除术的患者（222例单发性甲状旁腺疾病患者和13例多腺体疾病患者）。
在切除首个腺体后的基线、时间点1（约5分钟）和时间点2（约10分钟）进行术中甲状旁腺激素水平分析。
计算时间点1和时间点2的平均斜率，并使用方差分析以及Fisher最小显著差异事后检验进行分析，数据以基线术中甲状旁腺激素水平进行标准化，以比较单发性甲状旁腺疾病患者与多腺体疾病患者。创建基于回归的列线图以分析个体动力学衰减数据。
在时间点1（-0.91 [0.02] 对 -0.66 [0.05]；P<0.01）和时间点2（-0.77 [0.01] 对 -0.56 [0.05]；P<0.01）时，单发性甲状旁腺疾病的平均（SEM）斜率均显著陡于多腺体疾病的斜率。当使用从基线下降50%的标准阈值规则时，在时间点1，术中甲状旁腺激素值仅正确预测了23%的多腺体疾病患者（假阳性率为77%）。然而，列线图在时间点1正确预测了54%的多腺体疾病患者（假阳性率为46%）。在时间点2，标准阈值50%规则方法正确预测了38%的多腺体疾病患者（假阳性率为62%），而列线图仍正确分类了54%的多腺体疾病患者（假阳性率为46%）。
与标准的50%规则方法相比，基于回归的列线图逐步改善了对多腺体疾病的预测，并考虑了样本确切采集时间的变异性。斜率分析表明最早的时间点最能区分切除腺体的动力学情况。该列线图需要进行前瞻性验证。
