One of the main reasons for cancer screening is the early detection of local tumors to reduce cancer mortality. The belief or prediction that early detection reduces the likelihood of advanced stage cancer is called the “stage shift”. Unfortunately, platform movement does not consider positive issues after judgment. Furthermore, advanced stage cancer diagnosis with screening does not always reduce specific disease deaths. Reducing progressive cases at diagnosis will become organ-limited and will increase the number of cases eligible for metastasis. Also, advanced cases may reduce the incidence of metastatic disease at the time of diagnosis, leading to the same number of metastatic cases in a group with screening and non-screening.
To date, most population-based screening trials have examined the overall risk of metastasis in the screening and control arm during follow-up only at the time of diagnosis. Determining the effect of screening on metastasis can be difficult and time consuming; it requires following local issues in each test arm. Designing observed phase shift and case differences in disease support is at an advanced stage in developing practical, rational predictions and the impact of long-term screening. The Etzioni Group (Fred Hutch, Department of Public Health Sciences) developed a modeling framework to reduce the reduction in metastasis at diagnosis to a reduction in total metastasis under screening. This framework included data and assumptions that were important for the reasonable prediction of the long-term effects of screening. In the study, published in the Journal of Medical Screening, the researchers used the framework to project how a lower frequency of metastasis diagnosis would translate to and compare with overall metastasis frequency. the observed pattern of total metastasis from the test.
The modeling framework consists of three main components: stage-specific disease frequency at diagnosis with and without screening, excessive localization of cases in the screen arm to pre-diagnosis and non-diagnosis, and distribution of time from diagnosis to metastasis of non-invasive, local issues. European randomized data for Random Prostate Cancer (ERSPC) were used for platform movement and Scandanavian Prostate Cancer Group test data were used for metastatic progression risk. An ERSPC randomized controlled screening trial began in 1993 and compared Prostate Specific Antigen (PSA) screening every 2-4 years for adult males aged 55–69; this analysis used a total of 76,813 men (screening N = 36,270; control N = 40,543) from four centers of the ERSPC study. The SPCG-4 randomized controlled trial, initiated in 1989, began monitoring the progression of prostate cancer cases; a total of 695 men (intervention N = 347; control N = 348) were used in the study.
Fred Hutch’s microsimulation model of the natural history of prostate cancer was used to explain the frequency of de novo metastatic cancer. This model links individual PSA growth to onset and preclinical prostate tumor progression. For example, a man with a faster PSA growth rate may have a shorter time to clinical diagnosis and a higher likelihood of metastatic rate at diagnosis. Metastatic progression was predicted at the time of clinical diagnosis (screen arm). To analyze metastasis at diagnosis and total metastasis, the ratio of risk (time to metastasis), relative risk (ratio of metastasis rate measured at 12 years), overall risk (difference at 12 years) to use.
According to the simulation, there were fewer de novo metastatic cases at the time of diagnosis than the control arm. In the screen vs. arm arm of the 12-year simulated test, the relative risk was 0.57, the risk ratio was 0.60, and the overall risk reduction was 39.6 / 10,000 men. The effect of screening modeling on progressive metastasis in the screen and control arms showed a decrease in overall and relative benefit for total metastatic disease. In comparison, the symbolic test and ERSPC metastasis (at the time of diagnosis and overall) agreed.
Finally, the Etzioni group created a novel modeling framework to study the long-term effects of cancer screening on the frequency of metastasis. This model is more accurate than other predictions that use only phase shift at the time of diagnosis because the researchers measured de novo and positive issues. We know that screening reduces the number of advanced cases at diagnosis, but also increases the number of local undiagnosed cases with the potential for progression. Therefore, the expectations for platform-based screening benefits should be reduced when assessing disease mortality.
This research was supported by the National Cancer Institute, Cancer Intervention Network and Research Modeling.
Fred Hutch / UW Cancer Consortium member Ruth Etzioni contributed to this work.
Lange J, Remmers S, Gulati R, Bill-Axelson A, Johansson JE, Kwiatkowski M, Auvinen A, Hugosson J, Hu JC, Roobol MJ, Carlsson SV, Etzioni, R. Impact of cancer screening on metastasis: The cause of prostate cancer. study. Journal of Medical Screening. 2021 February 9. https://doi.org/10.1177/0969141321989738