Evidence-based impact projections of single-dose human papillomavirus vaccination in India: a modelling study.

BACKGROUND: Despite the high burden of cervical cancer, access to preventive measures remains low in India. A single-dose immunisation schedule could facilitate the scale-up of human papillomavirus (HPV) vaccination, contributing to global elimination of cervical cancer. We projected the effect of single-dose quadrivalent HPV vaccination in India in comparison with no vaccination or to a two-dose schedule. METHODS: In this modelling study, we adapted an HPV transmission model (EpiMetHeos) to Indian data on sexual behaviour (from the Demographic and Health Survey and the Indian National AIDS Control Organisation), HPV prevalence data (from two local surveys, from the states of Tamil Nadu and West Bengal), and cervical cancer incidence data (from Cancer Incidence in Five Continents for the period 2008-12 [volume XI], and the Indian National Centre for Disease Informatics and Research for the period 2012-16). Using the model, we projected the nationwide and state-specific effect of HPV vaccination on HPV prevalence and cervical cancer incidence, and lifetime risk of cervical cancer, for 100 years after the introduction of vaccination or in the first 50 vaccinated birth cohorts. Projections were derived under a two-dose vaccination scenario assuming life-long protection and under a single-dose vaccination scenario with protection duration assumptions derived from International Agency for Research on Cancer (IARC) India vaccine trial data, in combination with different vaccination coverages and catch-up vaccination age ranges. We used two thresholds to define cervical cancer elimination: an age-standardised incidence rate of less than 4 cases per 100 000 woman-years, and standardised lifetime risk of less than 250 cases per 100 000 women born. FINDINGS: Assuming vaccination in girls aged 10 years, with 90% coverage, and life-long protection by two-dose or single-dose schedule, HPV vaccination could reduce the prevalence of HPV16 and HPV18 infection by 97% (80% UI 96-99) in 50 years, and the lifetime risk of cervical cancer by 71-78% from 1067 cases per 100 000 women born under a no vaccination scenario to 311 (80% UI 284-339) cases per 100 000 women born in the short term and 233 (219-252) cases per 100 000 women born in the long term in vaccinated cohorts. Under this scenario, we projected that the age-standardised incidence rate threshold for elimination could be met across India (range across Indian states: 1·6 cases [80% UI 1·5-1·7] to 4·0 cases [3·8-4·4] per 100 000 woman-years), while the complementary threshold based on standardised lifetime risk was attainable in 17 (68%) of 25 states, but not nationwide (range across Indian states: 207 cases [80% UI 194-223] to 477 cases [447-514] per 100 000 women born). Under the considered assumptions of waning vaccine protection, single-dose vaccination was projected to have a 21-100% higher per-dose efficiency than two-dose vaccination. Single-dose vaccination with catch-up for girls and women aged 11-20 years was more impactful than two-dose vaccination without catch-up, with reduction of 39-65% versus 38% in lifetime risk of cervical cancer across the ten catch-up birth cohorts and the first ten routine vaccination birth cohorts. INTERPRETATION: Our evidence-based projections suggest that scaling up cervical cancer prevention through single-dose HPV vaccination could substantially reduce cervical cancer burden in India. FUNDING: The Bill & Melinda Gates Foundation.

Summary statement on screening for prostate cancer in Europe.

The European Randomised Study of Screening for Prostate Cancer (ERSPC) showed that Prostate-Specific Antigen (PSA) based screening results in a significant prostate cancer mortality reduction. Although there are concerns on overdiagnosis and overtreatment, it has been shown that the benefits can outweigh the harms if screening is stopped in older ages to prevent overdiagnosis. A limited screening program (for example screening at ages 55-59 years), including active surveillance for men with low-risk tumors, can even be cost-saving, compared with testing in an opportunistic setting in the wrong ages, as currently in Europe. Further improvements are expected in the use of active surveillance and in discrimination between indolent and significant disease due to new biomarkers and magnetic resonance imaging. However, these future developments are no reason to postpone feasibility studies of high-quality PSA screening and reduce opportunistic testing at old ages.

Comparative effectiveness of prostate cancer screening between the ages of 55 and 69 years followed by active surveillance.

BACKGROUND: Because of the recent grade C draft recommendation by the US Preventive Services Task Force (USPSTF) for prostate cancer screening between the ages of 55 and 69 years, there is a need to determine whether this could be cost-effective in a US population setting. METHODS: This study used a microsimulation model of screening and active surveillance (AS), based on data from the European Randomized Study of Screening for Prostate Cancer and the Surveillance, Epidemiology, and End Results Program, for the natural history of prostate cancer and Johns Hopkins AS cohort data to inform the probabilities of referral to treatment during AS. A cohort of 10 million men, based on US life tables, was simulated. The lifetime costs and effects of screening between the ages of 55 and 69 years with different screening frequencies and AS protocols were projected, and their cost-effectiveness was determined. RESULTS: Quadrennial screening between the ages of 55 and 69 years (55, 59, 63, and 67 years) with AS for men with low-risk cancers (ie, those with a Gleason score of 6 or lower) and yearly biopsies or triennial biopsies resulted in an incremental cost per quality-adjusted life-year (QALY) of $51,918 or $69,380, respectively. Most policies in which screening was followed by immediate treatment were dominated. In most sensitivity analyses, this study found a policy with which the cost per QALY remained below $100,000. CONCLUSIONS: Prostate-specific antigen-based prostate cancer screening in the United States between the ages of 55 and 69 years, as recommended by the USPSTF, may be cost-effective at a $100,000 threshold but only with a quadrennial screening frequency and with AS offered to all low-risk men. Cancer 2018;124:507-13. © 2017 American Cancer Society.

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.

Reconciling the Effects of Screening on Prostate Cancer Mortality in the ERSPC and PLCO Trials.

BACKGROUND: The ERSPC (European Randomized Study of Screening for Prostate Cancer) found that screening reduced prostate cancer mortality, but the PLCO (Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial) found no reduction. OBJECTIVE: To evaluate whether effects of screening on prostate cancer mortality relative to no screening differed between the ERSPC and PLCO. DESIGN: Cox regression of prostate cancer death in each trial group, adjusted for age and trial. Extended analyses accounted for increased incidence due to screening and diagnostic work-up in each group via mean lead times (MLTs), which were estimated empirically and using analytic or microsimulation models. SETTING: Randomized controlled trials in Europe and the United States. PARTICIPANTS: Men aged 55 to 69 (ERSPC) or 55 to 74 (PLCO) years at randomization. INTERVENTION: Prostate cancer screening. MEASUREMENTS: Prostate cancer incidence and survival from randomization; prostate cancer incidence in the United States before screening began. RESULTS: Estimated MLTs were similar in the ERSPC and PLCO intervention groups but were longer in the PLCO control group than the ERSPC control group. Extended analyses found no evidence that effects of screening differed between trials (P = 0.37 to 0.47 [range across MLT estimation approaches]) but strong evidence that benefit increased with MLT (P = 0.0027 to 0.0032). Screening was estimated to confer a 7% to 9% reduction in the risk for prostate cancer death per year of MLT. This translated into estimates of 25% to 31% and 27% to 32% lower risk for prostate cancer death with screening as performed in the ERSPC and PLCO intervention groups, respectively, compared with no screening. LIMITATION: The MLT is a simple metric of screening and diagnostic work-up. CONCLUSION: After differences in implementation and settings are accounted for, the ERSPC and PLCO provide compatible evidence that screening reduces prostate cancer mortality. PRIMARY FUNDING SOURCE: National Cancer Institute.

When should active surveillance for prostate cancer stop if no progression is detected?

BACKGROUND: A significant proportion of screen-detected men with prostate cancer may be overdiagnosed. Active Surveillance (AS) has emerged as a way to mitigate this problem, by delaying treatment of men, who are at low-risk until this becomes necessary. However, it is not known after how much time or biopsy rounds should patients stop AS and transition to conservative management (CM), if no progression is detected. METHODS: We used a microsimulation model with natural history of prostate cancer based on ERSPC and SEER data. We modeled referral to treatment while in AS, based on Johns Hopkins treatment-free survival data. We projected lifetime costs and effects of AS (and radical treatment, if progression is detected) under different biopsy follow-up schedules compared to CM, where radical treatment only occurs when men would be clinically diagnosed in absence of screening. RESULTS: For men with low-risk disease in younger age groups (55-65), AS is cost-effective for up to 7 yearly biopsy rounds. For men older than 65, even one biopsy round results in quality adjusted life years (QALYs) lost, though it may result in QALYs gained for men without previous screening. For men with intermediate-risk disease AS is cost-effective even for men in 65-75 age group. CONCLUSIONS: The benefit of AS when compared to CM is strongly dependent on life expectancy and disease risk. Clinicians should take this into account when selecting men to AS, deciding on biopsy frequency and when to stop AS surveillance rounds and transition to CM.

Is prostate cancer different in black men? Answers from 3 natural history models.

BACKGROUND: Black men in the United States have substantially higher prostate cancer incidence rates than the general population. The extent to which this incidence disparity is because prostate cancer is more prevalent, more aggressive, and/or more frequently diagnosed in black men is unknown. METHODS: The authors estimated 3 independently developed models of prostate cancer natural history in black men and in the general population using an updated reconstruction of prostate-specific antigen screening, based on the National Health Interview Survey in 2005 and on prostate cancer incidence data from the Surveillance, Epidemiology, and End Results program during 1975 through 2000. By using the estimated models, the natural history of prostate cancer was compared between black men and the general population. RESULTS: The models projected that from 30% to 43% (range across models) of black men develop preclinical prostate cancer by age 85 years, a risk that is (relatively) 28% to 56% higher than that in the general population. Among men who had preclinical disease onset, black men had a similar risk of diagnosis (range, 35%-49%) compared with the general population (32%-44%), but their risk of progression to metastatic disease by the time of diagnosis was from 44% to 75% higher than that in the general population. CONCLUSIONS: Prostate cancer incidence patterns implicate higher incidence of preclinical disease and higher risk of metastatic progression among black men. The findings suggest screening black men earlier than white men and support further research into the benefit-harm tradeoffs of more aggressive screening policies for black men. Cancer 2017;123:2312-2319. © 2017 American Cancer Society.

Estimating the risks and benefits of active surveillance protocols for prostate cancer: a microsimulation study.

OBJECTIVE: To estimate the increase in prostate cancer mortality (PCM) and the reduction in overtreatment resulting from different active surveillance (AS) protocols, compared with treating men immediately. PATIENTS AND METHODS: We used a microsimulation model (MISCAN-Prostate), with the natural history of prostate cancer based on European Randomized Study of Screening for Prostate Cancer data. We estimated the probabilities of referral to radical treatment while on AS, depending on disease stage, using data from the Johns Hopkins AS cohort. We sampled 10 million men, representative of the US population, and projected the effects of applying AS protocols that differed by time between biopsies and compared these with the effects of treating men immediately. RESULTS: We found that AS with yearly follow-up biopsies for men with low-risk prostate cancer (≤ T2a stage and Gleason 6) increases the probability of PCM to 2.6% (1% increase) and reduces overtreatment from 2.5 to 2.1% (18.4% reduction). With biopsies every 3 years after the first year, PCM increases by 2.3% and overtreatment reduces from 2.5 to 1.9% (30.3% reduction). The inclusion of men in the intermediate-risk group (> T2a stage or Gleason 3+4) in AS protocols increases PCM by 2.7% and reduces overtreatment from 2.5 to 2.0% (23.1% reduction). These results may not apply to African-American men. CONCLUSIONS: Offering AS to men with low-risk prostate cancer is relatively safe. Increasing the biopsy interval from yearly to up to every 3 years after the first year will significantly reduce overtreatment among men in the low-risk group, with limited PCM risk.

Estimating the individual benefit of immediate treatment or active surveillance for prostate cancer after screen-detection in older (65+) men.

A significant proportion of screen-detected men with prostate cancer is likely to be overtreated, especially in older age groups. We aim to find which groups of screen-detected older men (65+) benefit the most from Immediate Radical Treatment or Active Surveillance (AS) for prostate cancer, depending on age, screening history, health status and prostate cancer stage at detection. We used a microsimulation model (MISCAN) of the natural history of prostate cancer based on ERSPC data. Individual life histories are simulated with US comorbidity lifetables based on a random sample of MEDICARE data. Different screening histories are simulated and we count outcomes for men screen-detected from ages 66 to 72. For immediately treated men with low-risk disease (≤ T2a, Gleason 6) the probability of overtreatment ranges from 61% to 86% decreasing to between 37 and 46%, if they are assigned to AS. For intermediate risk men (≤ T2, Gleason 3 + 4) overtreatment ranges from 23 to 60%, which reduces to between 16 and 31% for AS. For high risk men (T3, or ≥ Gleason 4 + 3), overtreatment ranges from 11 to 51%. The disease stage at screen-detection is a critical risk factor for overtreatment. For low risk men, AS seems to significantly reduce overtreatment at a modest cost. For intermediate risk men, the decision between immediate treatment or AS depends on age and comorbidity status. Men screen-detected in a high risk disease stage may benefit from immediate treatment even beyond age 69.

Estimating the harms and benefits of prostate cancer screening as used in common practice versus recommended good practice: A microsimulation screening analysis.

BACKGROUND: Prostate-specific antigen (PSA) screening and concomitant treatment can be implemented in several ways. The authors investigated how the net benefit of PSA screening varies between common practice versus "good practice." METHODS: Microsimulation screening analysis (MISCAN) was used to evaluate the effect on quality-adjusted life-years (QALYs) if 4 recommendations were followed: limited screening in older men, selective biopsy in men with elevated PSA, active surveillance for low-risk tumors, and treatment preferentially delivered at high-volume centers. Outcomes were compared with a base model in which annual screening started at ages 55 to 69 years and were simulated using data from the European Randomized Study of Screening for Prostate Cancer. RESULTS: In terms of QALYs gained compared with no screening, for 1000 screened men who were followed over their lifetime, recommended good practice led to 73 life-years (LYs) and 74 QALYs gained compared with 73 LYs and 56 QALYs for the base model. In contrast, common practice led to 78 LYs gained but only 19 QALYs gained, for a greater than 75% relative reduction in QALYs gained from unadjusted LYs gained. The poor outcomes for common practice were influenced predominantly by the use of aggressive treatment for men with low-risk disease, and PSA testing in older men also strongly reduced potential QALY gains. CONCLUSIONS: Commonly used PSA screening and treatment practices are associated with little net benefit. Following a few straightforward clinical recommendations, particularly greater use of active surveillance for low-risk disease and reducing screening in older men, would lead to an almost 4-fold increase in the net benefit of prostate cancer screening. Cancer 2016;122:3386-3393. © 2016 American Cancer Society.

Screening for prostate cancer in the US? Reduce the harms and keep the benefit.

While the benefit of prostate-specific antigen (PSA) based screening is uncertain, a significant proportion of screen-detected cases is overdiagnosed. In order to make screening worthwhile, it is necessary to find policies that minimize overdiagnosis, without significantly increasing prostate cancer mortality (PCM). Using a microsimulation model (MISCAN) we project the outcomes of 83 screening policies in the US population, with different start and stop ages, screening frequencies, strategies where the PSA value changes the screening frequency, and strategies in which the PSA threshold (PSAt) increases with age. In the basecase strategy, yearly screening 50-74 with a PSAt of 3, the lifetime risk of PCM and overdiagnosis equals, respectively, 2.4 and 3.8%. The policies that reduce overdiagnosis the most (for maximum PCM increases relative to basecase of 1%, 3%, and 5%, respectively) are with a PSAt of 3, (1) yearly screening 50-74 where, if PSA <1 at age 65 or older, frequency becomes 4 years, with 3.6% (5.9% reduction), (2) 2-year screening 50-72, with 2.9% (24.3% reduction), and (3) yearly screening 50-70 (PSAt of 4 after age 66), with 2.2% (43.4% reduction). Stopping screening at age 70 is a reasonable way to reduce the harms and keep the benefit. Decreasing the stopping age has a larger effect on overdiagnosis reduction than reducing the screen frequency. Screening policies where the frequency of screening depends on PSA result or in which the PSAt changes with age did not substantially improve the balance of harms and benefits relative to simple yearly screening.

Personalizing age of cancer screening cessation based on comorbid conditions: model estimates of harms and benefits.

BACKGROUND: Harms and benefits of cancer screening depend on age and comorbid conditions, but reliable estimates are lacking. OBJECTIVE: To estimate the harms and benefits of cancer screening by age and comorbid conditions to inform decisions about screening cessation. DESIGN: Collaborative modeling with 7 cancer simulation models and common data on average and comorbid condition level-specific life expectancy. SETTING: U.S. population. PATIENTS: U.S. cohorts aged 66 to 90 years in 2010 with average health or 1 of 4 comorbid condition levels: none, mild, moderate, or severe. INTERVENTION: Mammography, prostate-specific antigen testing, or fecal immunochemical testing. MEASUREMENTS: Lifetime cancer deaths prevented and life-years gained (benefits); false-positive test results and overdiagnosed cancer cases (harms). For each comorbid condition level, the age at which harms and benefits of screening were similar to that for persons with average health having screening at age 74 years. RESULTS: Screening 1000 women with average life expectancy at age 74 years for breast cancer resulted in 79 to 96 (range across models) false-positive results, 0.5 to 0.8 overdiagnosed cancer cases, and 0.7 to 0.9 prevented cancer deaths. Although absolute numbers of harms and benefits differed across cancer sites, the ages at which to cease screening were consistent across models and cancer sites. For persons with no, mild, moderate, and severe comorbid conditions, screening until ages 76, 74, 72, and 66 years, respectively, resulted in harms and benefits similar to average-health persons. LIMITATION: Comorbid conditions influenced only life expectancy. CONCLUSION: Comorbid conditions are an important determinant of harms and benefits of screening. Estimates of screening benefits and harms by comorbid condition can inform discussions between providers and patients about personalizing screening cessation decisions. PRIMARY FUNDING SOURCE: National Cancer Institute and Centers for Disease Control and Prevention.

Choosing a Metamodel of a Simulation Model for Uncertainty Quantification.

BACKGROUND: Metamodeling may substantially reduce the computational expense of individual-level state transition simulation models (IL-STM) for calibration, uncertainty quantification, and health policy evaluation. However, because of the lack of guidance and readily available computer code, metamodels are still not widely used in health economics and public health. In this study, we provide guidance on how to choose a metamodel for uncertainty quantification. METHODS: We built a simulation study to evaluate the prediction accuracy and computational expense of metamodels for uncertainty quantification using life-years gained (LYG) by treatment as the IL-STM outcome. We analyzed how metamodel accuracy changes with the characteristics of the simulation model using a linear model (LM), Gaussian process regression (GP), generalized additive models (GAMs), and artificial neural networks (ANNs). Finally, we tested these metamodels in a case study consisting of a probabilistic analysis of a lung cancer IL-STM. RESULTS: In a scenario with low uncertainty in model parameters (i.e., small confidence interval), sufficient numbers of simulated life histories, and simulation model runs, commonly used metamodels (LM, ANNs, GAMs, and GP) have similar, good accuracy, with errors smaller than 1% for predicting LYG. With a higher level of uncertainty in model parameters, the prediction accuracy of GP and ANN is superior to LM. In the case study, we found that in the worst case, the best metamodel had an error of about 2.1%. CONCLUSION: To obtain good prediction accuracy, in an efficient way, we recommend starting with LM, and if the resulting accuracy is insufficient, we recommend trying ANNs and eventually also GP regression.

Evaluating Parameter Uncertainty in a Simulation Model of Cancer Using Emulators.

Background. Microsimulation models have been extensively used in the field of cancer modeling. However, there is substantial uncertainty regarding estimates from these models, for example, overdiagnosis in prostate cancer. This is usually not thoroughly examined due to the high computational effort required. Objective. To quantify uncertainty in model outcomes due to uncertainty in model parameters, using a computationally efficient emulator (Gaussian process regression) instead of the model. Methods. We use a microsimulation model of prostate cancer (microsimulation screening analysis [MISCAN]) to simulate individual life histories. We analyze the effect of parametric uncertainty on overdiagnosis with probabilistic sensitivity analyses (ProbSAs). To minimize the number of MISCAN runs needed for ProbSAs, we emulate MISCAN, using data pairs of parameter values and outcomes to fit a Gaussian process regression model. We evaluate to what extent the emulator accurately reproduces MISCAN by computing its prediction error. Results. Using an emulator instead of MISCAN, we may reduce the computation time necessary to run a ProbSA by more than 85%. The average relative prediction error of the emulator for overdiagnosis equaled 1.7%. We predicted that 42% of screen-detected men are overdiagnosed, with an associated empirical confidence interval between 38% and 48%. Sensitivity analyses show that the accuracy of the emulator is sensitive to which model parameters are included in the training runs. Conclusions. For a computationally expensive simulation model with a large number of parameters, we show it is possible to conduct a ProbSA, within a reasonable computation time, by using a Gaussian process regression emulator instead of the original simulation model.