Objectives:We aimed to develop a novel non-linear statistical model integrating primary tumor features on baseline [18F]-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT), molecular subtype, and clinical data for treatment benefit prediction in women with newly diagnosed breast cancer using innovative statistical techniques, as opposed to conventional methodological approaches.Methods:In this single-center retrospective study, we conducted a comprehensive assessment of women newly diagnosed with breast cancer who had undergone a FDG-PET/CT scan for staging prior to treatment. Primary tumor (PT) volume, maximum and mean standardized uptake value (SUVmax and SUVmean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were measured on PET/CT. Clinical data including clinical staging (TNM) but also PT anatomical site, histology, receptor status, proliferation index, and molecular subtype were obtained from the medical records. Overall survival (OS), progression-free survival (PFS), and clinical benefit (CB) were assessed as endpoints. A logistic generalized additive model was chosen as the statistical approach to assess the impact of all listed variables on CB.Results:70 women with newly diagnosed breast cancer (mean age 63.3 ± 15.4 years) were included. The most common location of breast cancer was the upper outer quadrant (40.0%) in the left breast (52.9%). An invasive ductal adenocarcinoma (88.6%) with a high tumor proliferation index (mean ki-67 expression 35.1 ± 24.5%) and molecular subtype B (51.4%) was by far the most detected breast tumor. Most PTs displayed on hybrid imaging a greater volume (12.8 ± 30.4 cm3) with hypermetabolism (mean ± SD of PT maximum SUVmax, SUVmean, MTV, and TLG, respectively: 8.1 ± 7.2, 4.9 ± 4.4, 12.7 ± 30.4, and 47.4 ± 80.2). Higher PT volume (p< 0.01), SUVmax (p= 0.04), SUVmean (p= 0.03), and MTV (<0.01) significantly compromised CB. A considerable majority of patients survived throughout this period (92.8%), while five women died (7.2%). In fact, the OS was 31.7 ± 14.2 months and PFS was 30.2 ± 14.1 months. A multivariate prediction model for CB with excellent accuracy could be developed using age, body mass index (BMI), T, M, PT TLG, and PT volume as predictive parameters. PT volume and PT TLG demonstrated a significant influence on CB in lower ranges; however, beyond a specific cutoff value (respectively, 29.52 cm3for PT volume and 161.95 cm3for PT TLG), their impact on CB only reached negligible levels. Ultimately, the absence of distant metastasis M displayed a strong positive impact on CB far ahead of the tumor size T (standardized average estimate 0.88 vs. 0.4).Conclusions:Our results emphasized the pivotal role played by FDG-PET/CT prior to treatment in forecasting treatment outcomes in women newly diagnosed with breast cancer. Nevertheless, careful consideration is required when selecting the methodological approach, as our innovative statistical techniques unveiled non-linear influences of predictive biomarkers on treatment benefit, highlighting also the importance of early breast cancer diagnosis.
目的：本研究旨在开发一种新型非线性统计模型，该模型整合了基线[¹⁸F]-氟代脱氧葡萄糖正电子发射断层扫描/计算机断层扫描（FDG-PET/CT）上的原发肿瘤特征、分子亚型和临床数据，并采用创新的统计技术（而非传统方法学途径），用于预测新诊断乳腺癌女性的治疗获益。 方法：在这项单中心回顾性研究中，我们对新诊断乳腺癌并在治疗前接受FDG-PET/CT扫描进行分期的女性进行了全面评估。在PET/CT上测量了原发肿瘤（PT）体积、最大和平均标准化摄取值（SUVmax和SUVmean）、代谢肿瘤体积（MTV）以及总病灶糖酵解（TLG）。从医疗记录中获取了临床数据，包括临床分期（TNM），以及PT解剖部位、组织学、受体状态、增殖指数和分子亚型。将总生存期（OS）、无进展生存期（PFS）和临床获益（CB）作为终点进行评估。选择逻辑广义加性模型作为统计方法，以评估所有列出变量对CB的影响。 结果：共纳入70名新诊断乳腺癌女性（平均年龄63.3 ± 15.4岁）。乳腺癌最常见的部位是左乳外上象限（40.0%）（占左乳病例的52.9%）。迄今为止，最常见的检测到的乳腺肿瘤是具有高肿瘤增殖指数（平均ki-67表达35.1 ± 24.5%）和分子亚型B（51.4%）的浸润性导管腺癌（88.6%）。大多数PT在混合成像中显示体积较大（12.8 ± 30.4 cm³）且代谢亢进（PT的SUVmax、SUVmean、MTV和TLG的平均值±标准差分别为：8.1 ± 7.2、4.9 ± 4.4、12.7 ± 30.4和47.4 ± 80.2）。较高的PT体积（p < 0.01）、SUVmax（p = 0.04）、SUVmean（p = 0.03）和MTV（p < 0.01）显著损害CB。绝大多数患者在此期间存活（92.8%），而五名女性死亡（7.2%）。实际上，OS为31.7 ± 14.2个月，PFS为30.2 ± 14.1个月。可以使用年龄、体重指数（BMI）、T分期、M分期、PT TLG和PT体积作为预测参数，建立一个具有极佳准确性的CB多变量预测模型。PT体积和PT TLG在较低范围内对CB有显著影响；然而，超过特定截断值（分别为PT体积29.52 cm³和PT TLG 161.95 cm³）后，它们对CB的影响仅达到可忽略的水平。最终，无远处转移（M）对CB显示出远强于肿瘤大小（T）的强烈积极影响（标准化平均估计值0.88 vs. 0.4）。 结论：我们的结果强调了治疗前FDG-PET/CT在预测新诊断乳腺癌女性治疗结局中的关键作用。然而，在选择方法学途径时需要仔细考虑，因为我们的创新统计技术揭示了预测性生物标志物对治疗获益的非线性影响，同时也凸显了早期乳腺癌诊断的重要性。
肿瘤(癌症)患者之家