Chisholm E M, Marshall R J, Brown D, Cooper E H, Giles G R
Br J Cancer. 1986 Jan;53(1):53-7. doi: 10.1038/bjc.1986.8.
The roles of a self-completed symptom questionnaire and four biochemical markers of disease were assessed to determine risk for gastric and colorectal cancer from within a hospital population and a random population. Eight-six patients with cancer, 168 subjects with benign conditions of the stomach and large bowel and 720 individuals from the community at large were investigated. Multivariate analyses of the questionnaire and biochemical data were performed individually and in combination using a data set comprising 54 cancer subjects, 80 patients with benign disease and 200 random individuals. The most favourable predictive equation derived was then applied to the remaining data set to determine its efficacy. In the primary analyses the questionnaire data identified 32 (60%) cancers successfully and using the biochemical markers alone 36 (67%) patients were also correctly classified as cancer bearing. However, the combination of the questionnaire and marker data improved the sensitivity for cancer to 50 cancers detected (92%) (P less than 0.02). Using the predictive equation from this combination of data to identify risk in the second data set 28/32 (88%) cancers were correctly identified with only an 11% false positive rate. An 18 month follow-up for the non-cancer group has to date revealed only one cancer (ca. pancreas). In this limited study, multivariate analysis of questionnaire and biochemical marker data does successfully identify individuals at "high risk' of harbouring gastric or colorectal cancer within a symptomatic population and may have a role in determining priority for investigation for a symptomatic individual.
评估了一份自我填写的症状问卷和四种疾病生化标志物的作用,以确定医院人群和随机人群中胃癌和结直肠癌的风险。对86例癌症患者、168例胃和大肠良性疾病患者以及720名普通社区个体进行了调查。使用包含54名癌症患者、80名良性疾病患者和200名随机个体的数据集,分别对问卷和生化数据进行多变量分析,并将两者结合进行分析。然后将得出的最有利预测方程应用于其余数据集,以确定其有效性。在初步分析中,问卷数据成功识别出32例(60%)癌症,仅使用生化标志物时,也有36例(67%)患者被正确分类为患癌。然而,问卷和标志物数据相结合将癌症检测的敏感性提高到检测出50例癌症(92%)(P小于0.02)。使用该数据组合得出的预测方程来识别第二个数据集中的风险,28/32例(88%)癌症被正确识别,假阳性率仅为11%。对非癌症组进行的18个月随访至今仅发现1例癌症(约为胰腺癌)。在这项有限的研究中,对问卷和生化标志物数据进行多变量分析确实成功地识别出有症状人群中患胃癌或结直肠癌“高风险”的个体,并且可能在确定有症状个体的检查优先级方面发挥作用。