Netterberg Ida, Nielsen Elisabet I, Friberg Lena E, Karlsson Mats O
Department of Pharmaceutical Biosciences, Uppsala University, Box 591, 751 24, Uppsala, Sweden.
Cancer Chemother Pharmacol. 2017 Aug;80(2):343-353. doi: 10.1007/s00280-017-3366-x. Epub 2017 Jun 27.
To investigate whether a more frequent monitoring of the absolute neutrophil counts (ANC) during myelosuppressive chemotherapy, together with model-based predictions, can improve therapy management, compared to the limited clinical monitoring typically applied today.
Daily ANC in chemotherapy-treated cancer patients were simulated from a previously published population model describing docetaxel-induced myelosuppression. The simulated values were used to generate predictions of the individual ANC time-courses, given the myelosuppression model. The accuracy of the predicted ANC was evaluated under a range of conditions with reduced amount of ANC measurements.
The predictions were most accurate when more data were available for generating the predictions and when making short forecasts. The inaccuracy of ANC predictions was highest around nadir, although a high sensitivity (≥90%) was demonstrated to forecast Grade 4 neutropenia before it occurred. The time for a patient to recover to baseline could be well forecasted 6 days (±1 day) before the typical value occurred on day 17.
Daily monitoring of the ANC, together with model-based predictions, could improve anticancer drug treatment by identifying patients at risk for severe neutropenia and predicting when the next cycle could be initiated.
与目前通常采用的有限临床监测相比，研究在骨髓抑制性化疗期间更频繁地监测绝对中性粒细胞计数（ANC）并结合基于模型的预测是否能改善治疗管理。
从先前发表的描述多西他赛诱导的骨髓抑制的总体模型中模拟化疗治疗的癌症患者的每日ANC。给定骨髓抑制模型，模拟值用于生成个体ANC时间进程的预测。在减少ANC测量量的一系列条件下评估预测的ANC的准确性。
当有更多数据可用于生成预测以及进行短期预测时，预测最为准确。ANC预测的不准确性在最低点附近最高，尽管在4级中性粒细胞减少症发生前表现出高敏感性（≥90%）来进行预测。患者恢复到基线的时间可以在第17天典型值出现前6天（±1天）得到很好的预测。
每日监测ANC并结合基于模型的预测，可以通过识别有严重中性粒细胞减少风险的患者并预测何时可以开始下一个周期来改善抗癌药物治疗。
