Purpose

Whether brain connectomics can predict 1-year decreased Quality of Life (QoL) in patients with breast cancer are unclear. A longitudinal study was utilized to explore their prediction abilities with a multi-center sample.

Methods

232 breast cancer patients were consecutively enrolled and 214 completed the 1-year QoL assessment (92.2%). Resting state functional magnetic resonance imaging was collected before the treatment and a multivoxel pattern analysis (MVPA) was performed to differentiate whole-brain resting-state connectivity patterns. Net Reclassification Improvement (NRI) as well as Integrated Discrimination Improvement (IDI) were calculated to estimate the incremental value of brain connectomics over conventional risk factors.

Results

Paracingulate Gyrus, Superior Frontal Gyrus and Frontal Pole were three significant brain areas. Brain connectomics yielded 7.8–17.2% of AUC improvement in predicting 1-year decreased QoL. The NRI and IDI ranged from 20.27 to 54.05%, 13.21–33.34% respectively.

Conclusion

Brain connectomics contribute to a more accurate prediction of 1-year decreased QoL in breast cancer. Significant brain areas in the prefrontal lobe could be used as potential intervention targets (i.e., Cognitive Behavioral Group Therapy) to improve long-term QoL outcomes in breast cancer.

中文翻译：

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脑连接组学改善了对乳腺癌 1 年生活质量下降的预测：多体素模式分析

目的

脑连接组学是否可以预测乳腺癌患者一年内生活质量(QoL) 下降尚不清楚。采用纵向研究来探索他们对多中心样本的预测能力。

方法

连续入组232名乳腺癌患者，214名完成1年生活质量评估（92.2%）。在治疗前收集静息态功能磁共振成像，并进行多体素模式分析（MVPA）以区分全脑静息态连接模式。计算净重分类改进（NRI）和综合辨别改进（IDI）来估计脑连接组学相对于传统风险因素的增量价值。

结果

副扣带回、额上回和额极是三个重要的大脑区域。脑连接组学在预测 1 年生活质量下降方面取得了 7.8-17.2% 的 AUC 改善。NRI 和 IDI 分别为 20.27% 至 54.05%、13.21% 至 33.34%。

结论

脑连接组学有助于更准确地预测乳腺癌 1 年生活质量下降。前额叶的重要大脑区域可作为潜在的干预目标（即认知行为团体治疗），以改善乳腺癌的长期生活质量结果。