While early detection is its main advantage pitfalls have also been discussed such as the high number of false positive results.Ĭlassical testing methods predefine a fixed sample size in order to conclude on the parameter under consideration. The idea of an automatized search for spatially and temporally elevated cancer incidence has been debated in the past. However, this final step is known to be challenging due to several reasons such as complex disease etiology, long latency or human migration. A statistically significant elevation will be followed by further investigations to examine potential risk factor associations. ![]() A common measurement is the standardized incidence ratio (SIR) which relates the cancer-specific cases in a region to the number of expected cases based on the rate in an appropriate reference population. If a suspected elevated risk is reported, the corresponding spatial area will be explored. Recent cancer cluster detection practice is seldom prospective and rather initiated by requests by the public, physicians or health offices. So far, active cancer monitoring is not common practice in the country. In Germany, population-based cancer registries are responsible for further investigation in observed cancer clusters. ![]() The Center for Disease Control and Prevention (CDC) defines a cancer cluster as a greater-than-expected number of cancer cases that occurs within a group of people in a geographic area over a period of time. Inhomogeneous unit size could be addressed by a flexible choice of the test parameter related to the observation time.Ĭancer monitoring and cluster detection have been and still are publicly debated at international level. Future work might consider refinements of the geographical structure. ![]() The procedure showed some desirable properties and is ready to use for a few settings but demands adjustments for others. Sensitivity increased with the expected number of cases and the amount of risk and decreased with the size of the geographical unit. Hence, the number of false positives was lower than the chosen significance level suggested, leading to a high specificity. If the expected numbers of cases were low, the significance level was not fully exhausted. Performance strongly depended on the choice of the test parameter. Scenarios were constructed differing by the simulation of clusters, significance level and test parameter indicating a risk to be elevated. A two-stage monitoring procedure was then executed considering the standardized incidence ratio and sequential probability ratio test. Based on the population structure of Lower Saxony the mean number of cases of three diagnoses were randomly assigned to the geographical units during 2008–2012. ![]() MethodsĪ simulation study based on a predefined selection of cancer types, geographical unit and time period was set up. This study aims to assess the performance of a recently developed prospective cancer monitoring method and the statistical tools used, in particular the sequential probability ratio test in regard to specificity, sensitivity, observation time and heterogeneity of size of the geographical unit. Common cancer monitoring practice is seldom prospective and rather driven by public requests.
0 Comments
Leave a Reply. |