Purpose

To build multivariate models to assess correctly and efficiently the contribution of tumor characteristics on the rate of regression of choroidal melanomas after brachytherapy in a way that adjusts for confounding and takes into account variation in tumor regression patterns.

Design

Modeling of longitudinal observational data.

Participants

Ultrasound images from 330 of 388 consecutive choroidal melanomas (87%) irradiated from 2000 through 2008 at the Helsinki University Hospital, Helsinki, Finland, a national referral center.

Methods

Images were obtained with a 10-MHz B-scan during 3 years of follow-up. Change in tumor thickness and cross-sectional area were modeled using a polynomial growth-curve function in a nested mixed linear regression model considering regression pattern and tumor levels. Initial tumor dimensions, tumor–node–metastasis (TNM) stage, shape, ciliary body involvement, pigmentation, isotope, plaque size, detached muscles, and radiation parameters were considered as covariates.

Main Outcome Measures

Covariates that independently predict tumor regression.

Results

Initial tumor thickness, largest basal diameter, ciliary body involvement, TNM stage, tumor shape group, break in Bruch's membrane, having muscles detached, and radiation dose to tumor base predicted faster regression, whether considering all tumors or those that regressed in a pattern compatible with exponential decay. Dark brown pigmentation was associated with slower regression. In multivariate modeling, initial tumor thickness remained the predominant and robust predictor of tumor regression (P < 0.0001). In addition, use of ruthenium isotope as opposed to iodine isotope (P = 0.018) independently contributed to faster regression of tumor thickness. For both isotopes considered alone, initial tumor thickness was the sole clinical predictor of regression (P < 0.0001).

Conclusions

Regression of choroidal melanoma after brachytherapy was associated with several clinical tumor and treatment parameters, most of which were shown to reflect initial tumor size. An independent predictor of regression of tumor thickness was the isotope used. These 2 covariates need to be adjusted for when exploring the associations with the rate of regression of histopathologic or genetic features of the tumor. Our model allows such future analyses efficiently without matching.

中文翻译：

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近距离放射治疗后脉络膜黑色素瘤消退的临床预测因素

目的

建立多变量模型以正确和有效地评估近距离放射治疗后肿瘤特征对脉络膜黑色素瘤消退率的影响，以适应混淆的方式并考虑到肿瘤消退模式的变化。

设计

纵向观测数据的建模。

参加者

2000年至2008年，在国家赫尔辛基芬兰国家转诊中心的赫尔辛基大学医院接受了388例连续脉络膜黑色素瘤中330例的超声图像照射。

方法

在3年的随访期间，使用10-MHz B扫描获得了图像。在考虑回归模式和肿瘤水平的嵌套混合线性回归模型中，使用多项式增长曲线函数对肿瘤厚度和横截面积的变化进行建模。初始肿瘤尺寸，肿瘤-淋巴结转移（TNM）阶段，形状，睫状体受累，色素沉着，同位素，斑块大小，肌肉分离和放射参数被认为是协变量。

主要观察指标

独立预测肿瘤消退的协变量。

结果

初始肿瘤厚度，最大基底直径，睫状体受累，TNM分期，肿瘤形状分组，布鲁赫膜破裂，肌肉分离以及对肿瘤基础的放射剂量，无论考虑所有肿瘤还是以兼容模式消退的肿瘤，均能更快地消退呈指数衰减 深褐色的色素沉着与较慢的退化有关。在多变量建模中，初始肿瘤厚度仍然是肿瘤消退的主要且有力的预测指标（P <0.0001）。另外，使用钌同位素而不是碘同位素（P  = 0.018）独立地有助于更快地消退肿瘤厚度。对于单独考虑的两种同位素，初始肿瘤厚度是回归的唯一临床预测指标（P <0.0001）。

结论

近距离放射治疗后脉络膜黑色素瘤的消退与几种临床肿瘤和治疗参数有关，其中大多数参数均反映了初始肿瘤的大小。所使用的同位素是肿瘤厚度消退的独立预测因子。当探索与肿瘤的组织病理学或遗传学特征的消退率的关联时，需要调整这两个协变量。我们的模型无需进行匹配即可有效地进行此类未来分析。