Hollen P J, Gralla R J, Cox C, Eberly S W, Kris M G
Northeastern University, College of Nursing, Boston, MA 02115, USA.
Lung Cancer. 1997 Oct;18(2):119-36. doi: 10.1016/s0169-5002(97)00059-7.
Despite the availability of several instruments to evaluate quality of life (QL) over time in patients with lung cancer, barriers in measurement remain. This methodological study used LCSS data (Lung Cancer Symptom Scale, a disease- and site-specific QL measure) to examine analysis methods to quantify QL where data needed for serial evaluation may be missing. Data from two large randomized trials, conducted at 30 centers, of a new combination chemotherapy regimen incorporating a new agent for patients (n = 673) with Stage III and IV non-small cell lung cancer were obtained for this study. QL had been prospectively measured at baseline, day 29, and every six weeks thereafter using the LCSS. For the slope analysis (SA) and area under the curve (AUC) analyses, an adjustment score of zero was used to indicate QL on the day of death (mortality adjustment) and each subsequent day until the end of the assessment period. Significant differences in QL, symptom scores and known prognostic factors at baseline were found in the attrition group. SA and AUC analysis allowed inclusion of 581 patients, giving an adequacy rate of 86%. By using a mortality adjustment, an additional 45 patients were included, increasing the inclusion rate to 93%. With the use of the mortality adjustment, QL was shown to decline over the interval, as opposed to rise if the adjustment had not been performed. The conclusions of the study were: (1) analysis for serial data using SA and AUC provides useful, but differing information; (2) when attrition (caused by death) is a factor, a mortality adjustment presented a more accurate assessment of QL as an endpoint; (3) more frequent evaluations of QL will capture rapid changes in patient status and reduce the attrition bias; (4) all patients should be followed until they die; and (5) QL should be given full consideration as a primary endpoint separate from survival.
尽管有多种工具可用于评估肺癌患者随时间变化的生活质量(QL),但测量方面仍存在障碍。这项方法学研究使用肺癌症状量表(LCSS,一种针对疾病和部位的QL测量工具)的数据,来研究在可能缺少系列评估所需数据的情况下量化QL的分析方法。本研究获取了在30个中心进行的两项大型随机试验的数据,这两项试验针对Ⅲ期和Ⅳ期非小细胞肺癌患者(n = 673)采用了一种包含新型药物的新联合化疗方案。使用LCSS在基线、第29天以及此后每六周对QL进行前瞻性测量。对于斜率分析(SA)和曲线下面积(AUC)分析,使用零调整分数来表示死亡日(死亡率调整)及之后直至评估期结束的每一天的QL。在失访组中发现基线时QL、症状评分和已知预后因素存在显著差异。SA和AUC分析纳入了581名患者,纳入率为86%。通过使用死亡率调整,又纳入了45名患者,纳入率提高到93%。使用死亡率调整后,QL在该时间段内呈下降趋势,而未进行调整时则呈上升趋势。该研究的结论为:(1)使用SA和AUC对系列数据进行分析可提供有用但不同的信息;(2)当失访(由死亡导致)是一个因素时,死亡率调整能更准确地评估QL作为一个终点;(3)更频繁地评估QL将捕捉患者状态的快速变化并减少失访偏倚;(4)所有患者都应随访至死亡;(5)QL应作为与生存分开的主要终点得到充分考虑。