A System Dynamics Model of Serum Prostate-Specific Antigen Screening for Prostate Cancer

System dynamics modeling for cancer prevention and control: A systematic review

Cancer prevention and control requires consideration of complex interactions between multilevel factors. System dynamics modeling, which consists of diagramming and simulation approaches for understanding and managing such complexity, is being increasingly applied to cancer prevention and control, but the breadth, characteristics, and quality of these studies is not known. We searched PubMed, Scopus, APA PsycInfo, and eight peer-reviewed journals to identify cancer-related studies that used system dynamics modeling. A dual review process was used to determine eligibility. Included studies were assessed using quality criteria adapted from prior literature and mapped onto the cancer control continuum. Characteristics of studies and models were abstracted and qualitatively synthesized. 32 studies met our inclusion criteria. A mix of simulation and diagramming approaches were used to address diverse topics, including chemotherapy treatments (16%), interventions to reduce tobacco or e-cigarettes use (16%), and cancer risk from environmental contamination (13%). Models spanned all focus areas of the cancer control continuum, with treatment (44%), prevention (34%), and detection (31%) being the most common. The quality assessment of studies was low, particularly for simulation approaches. Diagramming-only studies more often used participatory approaches. Involvement of participants, description of model development processes, and proper calibration and validation of models showed the greatest room for improvement. System dynamics modeling can illustrate complex interactions and help identify potential interventions across the cancer control continuum. Prior efforts have been hampered by a lack of rigor and transparency regarding model development and testing. Supportive infrastructure for increasing awareness, accessibility, and further development of best practices of system dynamics for multidisciplinary cancer research is needed.

A System Dynamics Simulation Applied to Healthcare: A Systematic Review

In recent years, there has been significant interest in developing system dynamics simulation models to analyze complex healthcare problems. However, there is a lack of studies seeking to summarize the available papers in healthcare and present evidence on the effectiveness of system dynamics simulation in this area. The present paper draws on a systematic selection of published literature from 2000 to 2019, in order to form a comprehensive view of current applications of system dynamics methodology that address complex healthcare issues. The results indicate that the application of system dynamics has attracted significant attention from healthcare researchers since 2013. To date, articles on system dynamics have focused on a variety of healthcare topics. The most popular research areas among the reviewed papers included the topics of patient flow, obesity, workforce demand, and HIV/AIDS. Finally, the quality of the included papers was assessed based on a proposed ranking system, and ways to improve the system dynamics models' quality were discussed.

Personalized strategies in population screening for prostate cancer

This review discusses evidence for population-based screening with contemporary screening tools. In Europe, prostate-specific antigen (PSA)-based screening led to a relative reduction of prostate cancer (PCa) mortality, but also to a substantial amount of overdiagnosis and unnecessarily biopsies. Risk stratification based on a single variable (a clinical variable or based on the presence of a lesion on prostate imaging) or based on multivariable approaches can aid in reducing unnecessary prostate biopsies and overdiagnosis by selecting men who can benefit from further clinical assessment. Multivariable approaches include clinical variables, and biomarkers, often combined in risk calculators or nomograms. These risk calculators can also incorporate the result of MRI imaging. In general, as compared to a purely PSA based approach, the combination of relevant prebiopsy information results in superior selection of men at higher risk of harboring clinically significant prostate cancer. Currently, it is not possible to draw any conclusions on the superiority of these multivariable risk-based approaches since head-to-head comparisons are virtually lacking. Recently initiated large population-based screening studies in Finland, Germany and Sweden, incorporating various multivariable risk stratification approaches will hopefully give more insight in whether the harm-benefit ratio can be improved, that is, maintain (or improving) the ability to reduce metastatic disease and prostate cancer mortality while reducing harm caused by unnecessary testing and overdiagnosis including related overtreatment.

Is tuberculosis elimination a feasible goal in Colombia by 2050?

Colombia has an underreporting of 30% of the total cases, according to World Health Organization (WHO) estimations. In 2016, successful tuberculosis (TB) treatment rate was 70%, and the mortality rate ranged between 3.5% and 10%. In 2015, Colombia adopted and adapted the End TB strategy and set a target of 50% reduction in incidence and mortality by 2035 compared with 2015. The aims of this study were: To evaluate whether Colombia will be able to achieve the goals of TB incidence and mortality by 2050, using the current strategies; and whether the implementation of new screening, diagnosis and TB treatment strategies will allow to achieve those WHO targets. An ecological study was conducted using TB case-notification, successful treatment and mortality rates from the last 8 years (2009-17). System dynamics analysis was performed using simulated scenarios: (1) continuation with the same trends following the trajectory of the last 8 years (Status quo) and (2) modification of the targets between 2017 through 2050, assuming the implementation of multimodal strategies to increase the screening, to improve the early diagnosis and to improve the treatment adherence. Following the current strategies, it is projected that Colombia will not achieve the End TB strategy targets. Achieving the goal of TB incidence of 10/100 000 by 2050 will only be possible by implementing combined strategies for increasing screening of people with respiratory symptoms, improving access to rapid diagnostic tests and improving treatment adherence. Therefore, it is necessary to design and implement simultaneous strategies according to the population needs and resources, in order to stride towards the End TB targets.

Designing an Agent-Based Model Using Group Model Building: Application to Food Insecurity Patterns in a U.S. Midwestern Metropolitan City

Recent advances in computing resources have increased interest in systems modeling and population health. While group model building (GMB) has been effectively applied in developing system dynamics models (SD), few studies have used GMB for developing an agent-based model (ABM). This article explores the use of a GMB approach to develop an ABM focused on food insecurity. In our GMB workshops, we modified a set of the standard GMB scripts to develop and validate an ABM in collaboration with local experts and stakeholders. Based on this experience, we learned that GMB is a useful collaborative modeling platform for modelers and community experts to address local population health issues. We also provide suggestions for increasing the use of the GMB approach to develop rigorous, useful, and validated ABMs.

Prostate cancer screening: what can we learn from randomised trials?

In this article, the principle of randomised trials are first described and then prostate cancer screening trials published to date are evaluated based on these principles. A summary of the randomised prostate cancer screening is provided. The conclusion that can be made from the results of the screening trials, as well as limitations of the evidence and open questions are outlined in the end.

Prognostic factors of prostate cancer mortality in a Finnish randomized screening trial

OBJECTIVES

To identify the prognostic factors of prostate cancer death among patients enrolled in a Finnish prostate cancer screening trial.

METHODS

Data on TNM stage, Gleason score, serum prostate-specific antigen at diagnosis, comorbidity and primary treatment were collected from medical records, as well as date and cause of death from Statistics Finland. Four prognostic risk groups were defined based on TNM stage, Gleason score and prostate-specific antigen at diagnosis. Hazard ratios and their 95% confidence intervals for prostate cancer death were calculated using Cox regression and competing-risk analysis with follow up from randomization. The differences in the effects of prognostic factors were assessed using interaction terms.

RESULTS

The 15-year survival was significantly lower among cases in the control arm compared with the screening arm (0.90 vs 0.92). However, the survival advantage was limited to screen-detected cases (0.94 vs 0.91 in cases detected outside screening). The prognostic risk group was the strongest factor predicting survival in the control arm, but weaker in screen-detected cases. Advanced disease was associated with substantially poorer outcome in cases detected outside screening than in screen-detected disease. Primary treatment had a similar effect in all groups. Comorbidity had a small prognostic effect in the control arm only.

CONCLUSIONS

Prognostic factors had a different effect on the outcome of cases detected through screening as those diagnosed otherwise. A high diagnostic prostate-specific antigen and advanced disease carried a poor prognosis, especially among the cases detected outside screening, even when lead-time was eliminated. This shows that the screening resulted in earlier treatment among the cases in the screening arm.

The efficacy of prostate-specific antigen screening: Impact of key components in the ERSPC and PLCO trials

BACKGROUND

The European Randomized Study of Screening for Prostate Cancer (ERSPC) demonstrated that prostate-specific antigen (PSA) screening significantly reduced prostate cancer mortality (rate ratio, 0.79; 95% confidence interval, 0.69-0.91). The US Prostate, Lung, Colorectal, and Ovarian (PLCO) trial indicated no such reduction but had a wide 95% CI (rate ratio for prostate cancer mortality, 1.09; 95% CI, 0.87-1.36). Standard meta-analyses are unable to account for key differences between the trials that can impact the estimated effects of screening and the trials' point estimates.

METHODS

The authors calibrated 2 microsimulation models to individual-level incidence and mortality data from 238,936 men participating in the ERSPC and PLCO trials. A cure parameter for the underlying efficacy of screening was estimated by the models separately for each trial. The authors changed step-by-step major known differences in trial settings, including enrollment and attendance patterns, screening intervals, PSA thresholds, biopsy receipt, control arm contamination, and primary treatment, to reflect a more ideal protocol situation and differences between the trials.

RESULTS

Using the cure parameter estimated for the ERSPC, the models projected 19% to 21% and 6% to 8%, respectively, prostate cancer mortality reductions in the ERSPC and PLCO settings. Using this cure parameter, the models projected a reduction of 37% to 43% under annual screening with 100% attendance and biopsy compliance and no contamination. The cure parameter estimated for the PLCO trial was 0.

CONCLUSIONS

The observed cancer mortality reduction in screening trials appears to be highly sensitive to trial protocol and practice settings. Accounting for these differences, the efficacy of PSA screening in the PLCO setting is not necessarily inconsistent with ERSPC results. Cancer 2018;124:1197-206. © 2017 American Cancer Society.

Surface-enhanced Raman spectroscopy of serum accurately detects prostate cancer in patients with prostate-specific antigen levels of 4-10 ng/mL

The surface-enhanced Raman spectroscopy (SERS) of blood serum was investigated to differentiate between prostate cancer (PCa) and benign prostatic hyperplasia (BPH) in males with a prostate-specific antigen level of 4-10 ng/mL, so as to reduce unnecessary biopsies. A total of 240 SERS spectra from blood serum were acquired from 40 PCa subjects and 40 BPH subjects who had all received prostate biopsies and were given a pathological diagnosis. Multivariate statistical techniques, including principal component analysis (PCA) and linear discriminant analysis (LDA) diagnostic algorithms, were used to analyze the spectra data of serum from patients in control (CTR), PCa and BPH groups; results offered a sensitivity of 97.5%, a specificity of 100.0%, a precision of 100.0% and an accuracy of 99.2% for CTR; a sensitivity of 90.0%, a specificity of 97.5%, a precision of 94.7% and an accuracy of 98.3% for BPH; a sensitivity of 95.0%, a specificity of 93.8%, a precision of 88.4% and an accuracy of 94.2% for PCa. Similarly, this technique can significantly differentiate low- and high-risk PCa with an accuracy of 92.3%, a specificity of 95% and a sensitivity of 89.5%. The results suggest that analyzing blood serum using SERS combined with PCA-LDA diagnostic algorithms is a promising clinical tool for PCa diagnosis and assessment.

Estimate of Opportunistic Prostate Specific Antigen Testing in the Finnish Randomized Study of Screening for Prostate Cancer

PURPOSE

Screening for prostate cancer remains controversial, although ERSPC (European Randomized Study of Screening for Prostate Cancer) showed a 21% relative reduction in prostate cancer mortality. The Finnish Randomized Study of Screening for Prostate Cancer, which is the largest component of ERSPC, demonstrated a statistically nonsignificant 16% mortality benefit in a separate analysis. The purpose of this study was to estimate the degree of contamination in the control arm of the Finnish trial.

MATERIALS AND METHODS

Altogether 48,295 and 31,872 men were randomized to the control and screening arms, respectively. The screening period was 1996 to 2007. The extent of prostate specific antigen testing was analyzed retrospectively using laboratory databases. The incidence of T1c prostate cancer (impalpable prostate cancer detected by elevated prostate specific antigen) was determined from the national Finnish Cancer Registry.

RESULTS

Approximately 1.4% of men had undergone prostate specific antigen testing 1 to 3 years before randomization. By the first 4, 8 and 12 years of followup 18.1%, 47.7% and 62.7% of men in the control arm had undergone prostate specific antigen testing at least once and in the screening arm the proportions were 69.8%, 81.1% and 85.2%, respectively. The cumulative incidence of T1c prostate cancer was 6.1% in the screening arm and 4.5% in the control arm (RR 1.21, 95% CI 1.13-1.30).

CONCLUSIONS

A large proportion of men in the control arm had undergone a prostate specific antigen test during the 15-year followup. Contamination is likely to dilute differences in prostate cancer mortality between the arms in the Finnish screening trial.

A Social Ecological Model of Syndemic Risk affecting Women with and At-Risk for HIV in Impoverished Urban Communities

Syndemic risk is an ecological construct, defined by co-occurring interdependent socio-environmental, interpersonal and intrapersonal determinants. We posited syndemic risk to be a function of violence, substance use, perceived financial hardship, emotional distress and self-worth among women with and at-risk for HIV in an impoverished urban community. In order to better understand these interrelationships, we developed and validated a system dynamics (SD) model based upon peer-reviewed literature; secondary data analyses of a cohort dataset including women living with and at-risk of HIV in Bronx, NY (N = 620); and input from a Bronx-based community advisory board. Simulated model output revealed divergent levels and patterns of syndemic risk over time across different sample profiles. Outputs generated new insights about how to effectively explore multicomponent multi-level programs in order to strategically develop more effective services for this population. Specifically, the model indicated that effective multi-level interventions might bolster women's resilience by increasing self-worth, which may result in decreased perceived financial hardship and risk of violence. Overall, our stakeholder-informed model depicts how self-worth may be a major driver of vulnerability and a meaningful addition to syndemic theory affecting this population.