Sato Alicia H, Anderson Garnet L, Urban Nicole, McIntosh Martin W
Fred Hutchinson Cancer Research Center, Seattle, WA 90109, USA.
Cancer Biomark. 2006;2(3-4):151-62. doi: 10.3233/cbm-2006-23-407.
It may be possible to reduce cancer mortality by monitoring the concentrations of serum biomarkers over time in men and women to detect their cancer early, when it is most curable. The simplest approach to using a biomarker for screening is to sequentially use fixed thresholds as a means to determine an abnormal test (e.g., PSA exceeding 4 mg/ml, CA 125 exceeding 30 U/ml). Alternatives to the simplest single threshold (ST) rules include more sophisticated algorithms that make use of screening history that accumulates over time and determines abnormal tests using individualized reference ranges. Although in principle longitudinal algorithms should out perform fixed threshold rules, the actual benefit gained will depend on behavior of the biomarker, the screening algorithm, and the screening frequency. Little information has been available to help predict when conditions should compel the adoption of the more sophisticated algorithms and when conditions suggest the simpler algorithms should suffice, or indeed be preferred. In this manuscript we evaluate the conditions under which one should expect great benefit, and when one should not expect benefit, by comparing the ability of simple and complex algorithms to detect cancer early under a variety of biomarker behaviors and screening frequencies.
通过长期监测男性和女性血清生物标志物的浓度，在癌症最可治愈的早期阶段进行检测，有可能降低癌症死亡率。使用生物标志物进行筛查的最简单方法是依次使用固定阈值来确定检测结果异常（例如，前列腺特异性抗原超过4毫克/毫升，癌抗原125超过30单位/毫升）。除了最简单的单阈值（ST）规则外，还有更复杂的算法，这些算法利用随时间积累的筛查历史，并使用个性化参考范围来确定检测结果异常。虽然原则上纵向算法应该比固定阈值规则表现更好，但实际获得的益处将取决于生物标志物的行为、筛查算法和筛查频率。几乎没有可用信息来帮助预测在何种情况下应采用更复杂的算法，以及在何种情况下简单算法就足够了，甚至更可取。在本论文中，我们通过比较简单算法和复杂算法在各种生物标志物行为和筛查频率下早期检测癌症的能力，评估在哪些情况下有望获得巨大益处，以及在哪些情况下无法获得益处。
