The use of discriminant analysis to guide palliative treatment for lung cancer patients.
The use of discriminant analysis to guide palliative treatment for lung cancer patients.
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DOI：
10.1016/s0936-6555(05)80767-8
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发表时间：
1992-01-01
期刊：
影响因子：
--
通讯作者：
Ash, D
中科院分区：
文献类型：
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作者：
Thorogood, J;Bulman, A S;Ash, D
本研究的目的是为不能手术的非小细胞肺癌患者建立一个预后指标，该指标可以预测患者的生存期至3个月。这将使得对预后受隐匿性转移限制的患者给予较少的辐射剂量，从而降低治疗发病率并提高治疗率。收集了96例患者的18个已知预后因素的数据。体能状态、淋巴细胞计数、体重减轻和疾病程度是最具预测性的因素，并被合并为一个指数。采用逻辑判别分析给出生存至3个月的可能性的数值评分，范围从0（不太可能）到1（确定）。在第一组96例患者中，3个月前观察到16例死亡，其中6例为预测死亡。有一个假阳性预测。因此，预测的总体准确性为89%，特异性为99%。对第二组80名患者测量了相同的4个预后因素。19例在3个月前死亡，其中5例预测为假阳性，总准确率为80%，特异性为97%。生存概率小于或等于0.2，尽管具有高度特异性，但仅适用于9%的患者，这是该试验临床有用性的限制因素。一个16-分支树形图允许任何患者在第一次就诊时根据四个预测因素被分配一个风险因素。使用该指数可以鼓励更合理的辐射剂量处方。
The aim of this study was to develop a prognostic index for patients with inoperable non-small cell lung cancer which could predict survival to 3 months. This would enable less radiation dose to be given to patients where prognosis is limited by occult metastases, giving rise to less treatment morbidity and raising the therapeutic ratio. Data on 18 known prognostic factors were collected on 96 patients. Performance status, lymphocyte count, weight loss and extent of disease were the most predictive factors and were combined into an index. Logistic discriminant analysis was employed to give a numerical score of likelihood of survival to 3 months, ranging from 0 (not likely) to 1 (certain). In this first set of 96 patients, 16 deaths were observed before 3 months, of which 6 were predicted. There was one false positive prediction. Overall accuracy of prediction was therefore 89% with 99% specificity. The same 4 prognostic factors were measured on a second set of 80 patients. Nineteen died before 3 months, of which 5 were predicted with 2 false positives, giving an overall accuracy of 80% and 97% specificity. A probability of survival of less than or equal to 0.2, although highly specific, was only applicable to 9% of patients and this was the limiting factor in the clinical usefulness of the test. A 16-branch tree diagram allows any patient to be assigned a risk factor based on the four predictive factors at the first clinic attendance. Use of the index could encourage more rational prescribing of radiation dose.