Stroke is a leading cause of disability, and language impairments (aphasia) after stroke are both common and particularly feared. Most stroke survivors with aphasia exhibit anomia (difficulties with naming common objects), but while many therapeutic interventions for anomia have been proposed, treatment effects are typically much larger in some patients than others. Here, we asked whether that variation might be more systematic, and even predictable, than previously thought. 18 patients, each at least 6 months after left hemisphere stroke, engaged in a computerised treatment for their anomia over a 6-week period. Using only: (a) the patients’ initial accuracy when naming (to-be) trained items; (b) the hours of therapy that they devoted to the therapy; and (c) whole-brain lesion location data, derived from structural MRI; we developed Partial Least Squares regression models to predict the patients’ improvements on treated items, and tested them in cross-validation. Somewhat surprisingly, the best model included only lesion location data and the hours of therapy undertaken. In cross-validation, this model significantly out-performed the null model, in which the prediction for each patient was simply the mean treatment effect of the group. This model also made promisingly accurate predictions in absolute terms: the correlation between empirical and predicted treatment response was 0.62 (95% CI 0.27, 0.95). Our results indicate that individuals’ variation in response to anomia treatment are, at least somewhat, systematic and predictable, from the interaction between where and how much lesion damage they have suffered, and the time they devoted to the therapy.

中风是导致残疾的主要原因，中风后的语言障碍（失语症）既常见又特别令人担忧。大多数患有失语症的中风幸存者表现出失语症（难以命名常见物体），但是虽然已经提出了许多针对失语症的治疗干预措施，但某些患者的治疗效果通常比其他患者大得多。在这里，我们询问这种变化是否比之前想象的更系统化，甚至更可预测。 18 名患者（每名患者均在左半球中风后至少 6 个月）在 6 周内接受了计算机化治疗，以治疗他们的贫血症。仅使用：（a）患者在命名（待）训练项目时的初始准确性； (b) 他们用于治疗的时间； (c) 来自结构 MRI 的全脑病变位置数据；我们开发了偏最小二乘回归模型来预测患者在治疗项目上的改善，并在交叉验证中对其进行测试。有点令人惊讶的是，最好的模型只包括病变位置数据和治疗时间。在交叉验证中，该模型显着优于零模型，其中每个患者的预测只是该组的平均治疗效果。该模型还做出了绝对准确的预测：经验治疗反应和预测治疗反应之间的相关性为 0.62 (95% CI 0.27, 0.95)。我们的研究结果表明，个体对贫血治疗反应的差异至少在某种程度上是系统性的和可预测的，这取决于他们所遭受的病变损伤的位置和程度以及他们投入治疗的时间之间的相互作用。