重症医学支持下指导肿瘤患者化疗的评分系统及检验指标的分析

目的对重症医学支持下指导肿瘤患者化疗的评分系统及检验指标进行分析，为临床选择适合的重症肿瘤患者进行化疗提供依据。 方法回顾性分析2010年1月至2016年12月在中山大学肿瘤防治中心住院期间因病情加重转入重症医学科（ICU）在重症医学技术支持下进行抗肿瘤化疗以改善肿瘤导致危重病情的44例肿瘤患者的临床资料。依据患者化疗后28 d的预后情况化分为死亡组（24例）、存活组（20例）。搜集患者入ICU后初始的各项肿瘤学评分系统［卡氏评分（KPS）、美国东部肿瘤协作组（ECOG）评分］及重症医学评分系统［急性生理与慢性健康评估（APACHEⅡ）、序贯器官功能衰竭评估（SOFA）、Logistic器官功能障碍评分（LODS）、多器官功能不全评分（MODS）、国家预警分数（NEWS）、系统炎症反应综合征（SIRS）、快速序贯器官功能衰竭评估（qSOFA）］的相关指标，并计算分值；以及患者化疗前的实验室检验结果、化疗期间的症状及支持手段，采用SPSS 22.0统计软件进行数据分析。 结果2组患者的肿瘤学评分系统及重症医学评分系统均未见明显统计学差异。化疗后死亡组的需要血管活性药物升压比例、丙氨酸氨基转移酶（ALT）、碱性磷酸酶（ALP）以及γ-谷氨酰转肽酶（GGT）均较存活组高，差异均具有统计学意义（P<0.05）。而其余指标未见明显统计学差异。将单因素分析后具有统计学意义的检验指标（需要血管活性药物升压比例、ALT、ALP、GGT）纳入多因素Logistic回归分析，发现需要血管活性药物升压比例（OR=12.306，95%CI：1.200~126.175）、ALP水平（OR=1.020，95%CI：1.003~1.039）为预测重症肿瘤患者化疗预后的独立危险因素。受试者工作特征（ROC）曲线分析显示，ALP的曲线下面积（AUC）为0.753，95%CI为0.605~0.901，P<0.05，截点值为86.25，敏感度为83.3％，特异度为70.0%。 结论进行化疗的重症肿瘤患者中，使用一般的肿瘤学评分系统或者一些重症医学评分系统均未能有效预测重症患者是否适合、可耐受化疗。血液肿瘤患者较实体肿瘤患者的预后存在优势。患者的肝功能相关指标可区分耐受化疗的重症肿瘤患者，而化疗期间是否使用血管活性药物升压、ALP则是判断重症肿瘤患者化疗预后的独立危险因素。

Analysis of scoring systems and test rating about chemotherapy for cancer patients supported by critical care medicine

Objectiveto analyze the scoring systems and test rating about chemotherapy for cancer patients supported by critical care medicine, hope to provide some clinical basis for the choice of chemotherapy for severe tumors. MethodsWe retrospectively analyzed the clinical data of 44 patients admitted to ICU and then given chemotherapy in ICU at the Sun Yat-sen University from January 2010 to December 2016. All patients were diagnosed as malignant tumors. According to the change of the patient′s condition after chemotherapy, they were divided into the worsening group (24) and the improvement group (20). The initial oncology scoring systems [Karnofsky (KPS), Eastern Cooperative Oncology Group (ECOG)] and intensive medical scoring systems [Acute Physiology and Chronic Health Evaluation 2 (APACHEⅡ), sequential organ failure assessment (SOFA), Logistic organ dysfunoction system (LODS), quick sequential organ failure assessment (qSOFA), multiple organ dysfunction score (MODS), systematic inflammatory response syndrome (SIRS) and National early warning score (NEWS)] were calculated with the relevant indexs; results of different scoring systems, the test results before chemotherapy, the symptoms during chemotherapy and supportive methods during chemotherapy were analyzed using SPSS 22.0 statistical software. ResultsThere was no significant difference between various scoring systems. The proportion of using vasoactive drugs to increase blood pressure, ALT, ALP and GGT in provement group were higher than these in worsening group. The differences were statistically significant (P<0.05). The proportion of using vasoactive drugs to increase blood pressure, ALT, ALP, GGT were included in multivariate analysis. It was found that ″using vasoactive drugs to increase blood pressure″ (OR=12.306, 95%CI: 1.200-126.175) and ALP (OR=1.020, 95%CI: 1.003-1.039) were independent risk factors for predicting the prognosis of critically ill cancer patients. The area under the curve (AUC) of ALP was 0.753, 95%CI: 0.605-0.901 with 86.25 of cut-off value, 83.3% of sensitivity, and 70.0% of specificity. ConclusionsIn ICU, general scoring system or severe medical scoring system are unable to predict whether severe patients are resistant to chemotherapy or would benef from chemotherapy. The prognosis of patients with hematologic malignancies is better than that of solid tumors. The liver function index of patients can be useful to predict the resistance to chemotherapy patients, ″using vasoactive drugs to increase blood pressure″ and ALP are the independent risk factors for prognosis after chemotherapy.