Decision makers often desire both guidance on the most cost-effective interventions given current knowledge and also the value of collecting additional information to improve the decisions made (i.e., from value of information [VOI] analysis). Unfortunately, VOI analysis remains underused due to the conceptual, mathematical, and computational challenges of implementing Bayesian decision-theoretic approaches in models of sufficient complexity for real-world decision making. In this study, we propose a novel practical approach for conducting VOI analysis using a combination of probabilistic sensitivity analysis, linear regression metamodeling, and unit normal loss integral function--a parametric approach to VOI analysis. We adopt a linear approximation and leverage a fundamental assumption of VOI analysis, which requires that all sources of prior uncertainties be accurately specified. We provide examples of the approach and show that the assumptions we make do not induce substantial bias but greatly reduce the computational time needed to perform VOI analysis. Our approach avoids the need to analytically solve or approximate joint Bayesian updating, requires only one set of probabilistic sensitivity analysis simulations, and can be applied in models with correlated input parameters.

BACKGROUND: Contralateral prophylactic mastectomy (CPM) rates have substantially increased in recent years and may reflect an exaggerated perceived benefit from the procedure. The objective of this study was to evaluate the magnitude of the survival benefit of CPM for women with unilateral breast cancer. METHODS: We developed a Markov model to simulate survival outcomes after CPM and no CPM among women with stage I or II breast cancer without a BRCA mutation. Probabilities for developing contralateral breast cancer (CBC), dying from CBC, dying from primary breast cancer, and age-specific mortality rates were estimated from published studies. We estimated life expectancy (LE) gain, 20-year overall survival, and disease-free survival with each intervention strategy among cohorts of women defined by age, estrogen receptor (ER) status, and stage of cancer. RESULTS: Predicted LE gain from CPM ranged from 0.13 to 0.59 years for women with stage I breast cancer and 0.08 to 0.29 years for those with stage II breast cancer. Absolute 20-year survival differences ranged from 0.56% to 0.94% for women with stage I breast cancer and 0.36% to 0.61% for women with stage II breast cancer. CPM was more beneficial among younger women, stage I, and ER-negative breast cancer. Sensitivity analyses yielded a maximum 20-year survival difference with CPM of only 1.45%. CONCLUSIONS: The absolute 20-year survival benefit from CPM was less than 1% among all age, ER status, and cancer stage groups. Estimates of LE gains and survival differences derived from decision models may provide more realistic expectations of CPM.

INTRODUCTION In the 1990s, several organizations began recommending evaluation of > 12 lymph nodes during colon resection because of its association with improved survival. We examined practice implications of multispecialty quality guidelines over the past 20 years recommending evaluation of ≥ 12 lymph nodes during colon resection for adequate staging. MATERIALS AND METHODS We used the 1988 to 2009 Surveillance, Epidemiology, and End Results program to conduct a retrospective observational cohort study of 90,203 surgically treated patients with colon cancer. We used Cochran-Armitage tests to examine trends in lymph node examination over time and multivariate logistic regression to identify patient characteristics associated with guideline-recommended lymph node evaluation. RESULTS The introduction of practice guidelines was associated with gradual increases in guideline-recommended lymph node evaluation. From 1988 to 1990, 34% of patients had > 12 lymph nodes evaluated, increasing to 38% in 1994 to 1996 and to > 75% from 2006 to 2009. Younger, white patients and those with more-extensive bowel penetration (T3/4 nonmetastatic) and high tumor grade saw more-rapid increases in lymph node evaluation (P < .001). Multivariate analyses demonstrated a significant interaction between year of diagnosis and both T stage and grade, indicating that those with higher T stage and higher grade were more likely to receive guideline-recommended care earlier. CONCLUSION The implementation of lymph node evaluation guidelines was accepted gradually into practice but adopted more quickly among higher risk patients. By identifying patients who are least likely to receive guideline-recommended care, these findings present a starting point for promoting targeted improvements in cancer care and further understanding underlying contributors to these disparities.

BACKGROUND: Over the past 20 years, surgical practice organizations have recommended the identification of >/=12 lymph nodes from surgically treated colon cancer patients as an indicator of quality performance for adequate staging; however, studies suggest that significant variation exists among hospitals in their level of adherence to this recommendation. We examined hospital-level factors that were associated with institutional improvement or maintenance of adequate lymph node evaluation after the introduction of surgical quality guidelines. RESEARCH DESIGN: Using the 1996-2007 SEER-Medicare data, we evaluated hospital characteristics associated with short-term (1999-2001), medium-term (2002-2004), and long-term (2005-2007) guideline-recommended (>/=12) lymph node evaluation compared with initial evaluation levels (1996-1998) using chi tests and multivariate logistic regression analysis, adjusting for patient case-mix. RESULTS: We identified 228 hospitals that performed >/=6 colon cancer surgeries during each study period from 1996-2007. In the initial study period (1996-1998), 26.3% (n=60) of hospitals were performing guideline-recommended evaluation, which increased to 28.1% in 1999-2001, 44.7% in 2002-2004, and 70.6% in 2005-2007. In multivariate analyses, a hospital's prior guideline performance [odds ratio (OR) (95% confidence interval (CI)): 4.02 (1.92, 8.42)], teaching status [OR (95% CI): 2.33 (1.03, 5.28)], and American College of Surgeon's Oncology Group membership [OR (95% CI): 3.39 (1.39, 8.31)] were significantly associated with short-term guideline-recommended lymph node evaluation. Prior hospital performance [OR (95% CI): 2.41 (1.17, 4.94)], urban location [OR (95% CI): 2.66 (1.12, 6.31)], and American College of Surgeon's Oncology Group membership [OR (95% CI): 6.05 (2.32, 15.77)] were associated with medium-term performance; however, these factors were not associated with long-term performance. CONCLUSIONS: Over the 12-year period, there were marked improvements in hospital performance for guideline-recommended lymph node evaluation. Understanding patterns in improvement over time contributes to debates over optimal designs of quality-improvement programs.

BACKGROUND / OBJECTIVE: Modelers lack a tool to systematically and clearly present complex model results, including those from sensitivity analyses. The objective was to propose linear regression metamodeling as a tool to increase transparency of decision analytic models and better communicate their results. METHODS: We used a simplified cancer cure model to demonstrate our approach. The model computed the lifetime cost and benefit of 3 treatment options for cancer patients. We simulated 10,000 cohorts in a probabilistic sensitivity analysis (PSA) and regressed the model outcomes on the standardized input parameter values in a set of regression analyses. We used the regression coefficients to describe measures of sensitivity analyses, including threshold and parameter sensitivity analyses. We also compared the results of the PSA to deterministic full-factorial and one-factor-at-a-time designs. RESULTS: The regression intercept represented the estimated base-case outcome, and the other coefficients described the relative parameter uncertainty in the model. We defined simple relationships that compute the average and incremental net benefit of each intervention. Metamodeling produced outputs similar to traditional deterministic 1-way or 2-way sensitivity analyses but was more reliable since it used all parameter values. CONCLUSIONS: Linear regression metamodeling is a simple, yet powerful, tool that can assist modelers in communicating model characteristics and sensitivity analyses.

BACKGROUND: Simulation models designed to evaluate cancer prevention strategies make assumptions on background mortality-the competing risk of death from causes other than the cancer being studied. Researchers often use the U.S. life tables and assume homogeneous other-cause mortality rates. However, this can lead to bias because common risk factors such as smoking and obesity also predispose individuals for deaths from other causes such as cardiovascular disease. METHODS: We obtained calendar year-, age-, and sex-specific other-cause mortality rates by removing deaths due to a specific cancer from U.S. all-cause life tables. Prevalence across 12 risk factor groups (3 smoking [never, past, and current smoker] and 4 body mass index [BMI] categories [<25, 25-30, 30-35, 35+ kg/m(2)]) were estimated from national surveys (National Health and Nutrition Examination Surveys [NHANES] 1971-2004). Using NHANES linked mortality data, we estimated hazard ratios for death by BMI/smoking using a Poisson regression model. Finally, we combined these results to create 12 sets of BMI and smoking-specific other-cause life tables for U.S. adults aged 40 years and older that can be used in simulation models of lung, colorectal, or breast cancer. RESULTS: We found substantial differences in background mortality when accounting for BMI and smoking. Ignoring the heterogeneity in background mortality in cancer simulation models can lead to underestimation of competing risk of deaths for higher-risk individuals (e.g., male, 60-year old, white obese smokers) by as high as 45%. CONCLUSION: Not properly accounting for competing risks of death may introduce bias when using simulation modeling to evaluate population health strategies for prevention, screening, or treatment. Further research is warranted on how these biases may affect cancer-screening strategies targeted at high-risk individuals.

BACKGROUND: Treatment options for colorectal cancer (CRC) have improved substantially over the past 25 years. Measuring the impact of these improvements on survival outcomes is challenging, however, against the background of overall survival gains from advancements in the prevention, screening, and treatment of other conditions. Relative survival is a metric that accounts for these concurrent changes, allowing assessment of changes in CRC survival. We describe stage- and location-specific trends in relative survival after CRC diagnosis. METHODS: We analyzed survival outcomes for 233965 people in the Surveillance Epidemiology and End Results (SEER) program who were diagnosed with CRC between January 1, 1975, and December 31, 2003. All models were adjusted for sex, race (black vs white), age at diagnosis, time since diagnosis, and diagnosis year. We estimated the proportional difference in survival for CRC patients compared with overall survival for age-, sex-, race-, and period-matched controls to account for concurrent changes in overall survival using two-sided Wald tests. RESULTS: We found statistically significant reductions in excess hazard of mortality from CRC in 2003 relative to 1975, with excess hazard ratios ranging from 0.75 (stage IV colon cancer; P < .001) to 0.32 (stage I rectal cancer; P < .001), indicating improvements in relative survival for all stages and cancer locations. These improvements occurred in earlier years for patients diagnosed with stage I cancers, with smaller but continuing improvements for later-stage cancers. CONCLUSIONS: Our results demonstrate a steady trend toward improved relative survival for CRC, indicating that treatment and surveillance improvements have had an impact at the population level.

BACKGROUND Among surgically treated patients with colon cancer, lower long-term mortality has been demonstrated in those with 12 or more lymph nodes evaluated. We examined whether patients receiving adequate lymph node evaluation were also more likely to receive comprehensive postsurgical care, leading to lower mortality. STUDY DESIGN We used the 1992 to 2007 Surveillance, Epidemiology, and End Results (SEER)-Medicare data to identify surgically treated American Joint Committee on Cancer (AJCC) stage III colon cancer patients. We used chi-square analyses and logistic regression to evaluate the association between adequate (≥12) lymph node evaluation and receipt of postsurgical care (adjuvant chemotherapy, surveillance colonoscopy, CT scans, and CEA testing) and Cox proportional hazards regression to evaluate 10-year all-cause mortality, adjusting for postsurgical care. RESULTS Among 17,906 surgically treated stage III colon cancer patients, adequate (≥12) lymph node evaluation was not associated with receiving comprehensive postsurgical care after adjustment for patient and tumor characteristics (p > 0.05 for all). Initially, adequate lymph node evaluation was associated with lower all-cause mortality (hazard ratio [HR] 0.88; 95% CI [0.85 to 0.91]), but among 3-year survivors, the impact of adequate lymph node evaluation on lower mortality was diminished (HR 0.94; 95% CI [0.88 to 1.01]). However, receiving comprehensive postsurgical care was associated with continued lower mortality in 3-year survivors. CONCLUSIONS Adequate lymph node evaluation for colon cancer was associated with lower mortality among all patients. However, among 3-year survivors, the association between lymph node evaluation and lower hazard of death was no longer significant, while postsurgical care remained strongly associated with lower long-term mortality, indicating that postsurgical care may partially explain the relationship between lymph node evaluation and mortality.

Models—mathematical frameworks that facilitate estimation of the consequences of health care decisions—have become essential tools for health technology assessment. Evolution of the methods since the first ISPOR modeling task force reported in 2003 has led to a new task force, jointly convened with the Society for Medical Decision Making, and this series of seven papers presents the updated recommendations for best practices in conceptualizing models; implementing state–transition approaches, discrete event simulations, or dynamic transmission models; dealing with uncertainty; and validating and reporting models transparently. This overview introduces the work of the task force, provides all the recommendations, and discusses some quandaries that require further elucidation. The audience for these papers includes those who build models, stakeholders who utilize their results, and, indeed, anyone concerned with the use of models to support decision making.

BACKGROUND: Considerable disparities exist in colorectal cancer (CRC) incidence and mortality rates between blacks and whites in the United States. We estimated how much of these disparities could be explained by differences in CRC screening and stage-specific relative CRC survival. METHODS: We used the MISCAN-Colon microsimulation model to estimate CRC incidence and mortality rates in blacks, aged 50 years and older, from 1975 to 2007 assuming they had: (i) the same trends in screening rates as whites instead of observed screening rates (incidence and mortality); (ii) the same trends in stage-specific relative CRC survival rates as whites instead of observed (mortality only); and (iii) a combination of both. The racial disparities in CRC incidence and mortality rates attributable to differences in screening and/or stage-specific relative CRC survival were then calculated by comparing rates from these scenarios to the observed black rates. RESULTS: Differences in screening accounted for 42% of disparity in CRC incidence and 19% of disparity in CRC mortality between blacks and whites. Thirty-six percent of the disparity in CRC mortality could be attributed to differences in stage-specific relative CRC survival. Together screening and survival explained a little more than 50% of the disparity in CRC mortality between blacks and whites. CONCLUSION: Differences in screening and relative CRC survival are responsible for a considerable proportion of the observed disparities in CRC incidence and mortality rates between blacks and whites. IMPACT: Enabling blacks to achieve equal access to care as whites could substantially reduce the racial disparities in CRC burden.