Outcomes and Utilization of Adjuvant Chemotherapy for Stage II Colon Cancer in the Oxaliplatin Period: A SEER-Medicare Analysis.

PURPOSE: Previous SEER (Surveillance, Epidemiology, and End Results)-Medicare analyses have shown no definitive survival benefit for adjuvant chemotherapy (AC) with fluoropyrimidines. Impact of oxaliplatin-containing regimens for elderly stage II patients in real-world setting is unknown. We explored the utilization and outcome of AC after the Food and Drug Administration (FDA) approval of oxaliplatin. PATIENTS AND METHODS: Patients with stage II colon cancer (2004-2011) who underwent resection were selected for this analysis. Medicare claims data were used to ascertain the administration of AC within 120 days after surgery. The primary endpoint of the analysis was overall survival. We used the Cox proportional hazards model to estimate the effect of AC while adjusting for clinical and sociodemographic variables available in SEER. To adjust for referral pattern, a source of selection bias, we conducted an instrumental variable analysis using the surgeon of record and health service area. RESULTS: A total of 16,468 patients were identified and 12.1% received AC. AC recipients were significantly younger, more likely to be male, nonwhite, married, and had lower comorbidity index. Their tumors had a more advanced stage, more likely to be left sided, and were less differentiated. The hazard ratio (HR) from the Cox model showed a statistically significant survival advantage for AC (HR=0.847, 95% confidence interval: 0.782-0.916). However, results from the instrumental variable analysis indicated that there was no definitive benefit of survival in AC recipients (HR=1.779, 95% confidence interval: 0.927-3.415). AC use decreased over time. CONCLUSIONS: After controlling for referral patterns, administration of AC provided no definitive survival benefit. Future studies may elucidate the elderly population who may benefit from AC.

Access to high-volume surgeons and the opportunity cost of performing radical prostatectomy by low-volume providers.

BACKGROUND: Evidence suggests that redirecting surgeries to high-volume providers may be associated with better outcomes and significant societal savings. Whether such referrals are feasible remains unanswered. METHODS: Medicare Provider Utilization and Payment Data, SEER 18, and US Incidence data were used to determine the geographic distribution and radical prostatectomy volume for providers. Access was defined as availability of a high-volume provider within driving distance of 100 miles. The opportunity cost was defined as the value of benefits achievable by performing the surgery by a high-volume provider that was forgone by not making a referral. The savings per referral were derived from a published Markov model for radical prostatectomy. RESULTS: A total of 14% of providers performed>27% of the radical prostatectomies with>30 cases per year and were designated high-volume providers. Providers with below-median volume (≤16 prostatectomies per year) performed>32% of radical prostatectomies. At least 47% of these were within a 100-mile driving distance (median = 22 miles), and therefore had access to a high-volume provider (>30 prostatectomies per year). This translated into a discounted savings of more than $24 million per year, representing the opportunity cost of not making a referral. The average volume for high- and low-volume providers was 55 and 13, respectively, resulting in an annual experience gap of 43 and a cumulative gap of 125 surgeries over 3 years. In 2014, the number of surgeons performing radical prostatectomy decreased by 5% while the number of high- and low-volume providers decreased by 25% and 11% showing a faster decline in the number of high-volume providers compared with low-volume surgeons. CONCLUSIONS: About half of prostatectomies performed by surgeons with below-median annual volume were within a 100-mile driving distance (median of 22 miles) of a high-volume surgeon. Such a referral may result in minimal additional costs and substantially improved outcomes.

Comparative effectiveness of screening strategies for colorectal cancer.

BACKGROUND: Screening for colorectal cancer (CRC) has been successful in decreasing the incidence and mortality from CRC. Although new screening tests have become available, their relative impact on CRC outcomes remains unexplored. This study compares the outcomes of various screening strategies on CRC outcomes. METHODS: A Markov model representing the natural history of CRC was built and validated against empiric data from screening trials as well as the Microstimulation Screening Analysis (MISCAN) model. Thirteen screening strategies based on colonoscopy, sigmoidoscopy, computed tomographic colonography, as well as fecal immunochemical, occult blood, and stool DNA testing were compared with no screening. A simulated sample of the US general population ages 50 to 75 years with an average risk of CRC was followed for up to 35 years or until death. Effectiveness was measured by discounted life years gained and the number of CRCs prevented. Discounted costs and cost-effectiveness ratios were calculated. A discount rate of 3% was used in calculations. The study took a societal perspective. RESULTS: Colonoscopy emerged as the most effective screening strategy with the highest life years gained (0.022 life years) and CRCs prevented (n = 1068) and the lowest total costs ($2861). These values were 0.012 life years gained, 574 CRCs prevented, and a total cost of $3164, respectively, for FOBT; and 0.011 life years gained, 647 CRCs prevented, and a total cost of $4296, respectively, for DNA testing. Improved sensitivity or specificity of a screening test for CRC detection was not sufficient to close the outcomes gap compared with colonoscopy. CONCLUSIONS: Improvement in CRC-detection performance is not sufficient to improve screening outcomes. Special attention must be directed to detecting precancerous adenomas. Cancer 2017;123:1516-1527. © 2017 American Cancer Society.

Comparative effectiveness of screening strategies for Lynch syndrome.

BACKGROUND: Colorectal cancer is the second leading cause of cancer death in the United States. Approximately 3% of colorectal cancers are associated with Lynch Syndrome. Controversy exists regarding the optimal screening strategy for Lynch Syndrome. METHODS: Using an individual level microsimulation of a population affected by Lynch syndrome over several years, effectiveness and cost-effectiveness of 21 screening strategies were compared. Modeling assumptions were based upon published literature, and sensitivity analyses were performed for key assumptions. In a two-step process, the number of Lynch syndrome diagnoses (Step 1) and life-years gained as a result of foreknowledge of Lynch syndrome in otherwise healthy carriers (Step 2) were measured. RESULTS: The optimal strategy was sequential screening for probands starting with a predictive model, then immunohistochemistry for mismatch repair protein expression (IHC), followed by germline mutation testing (incremental cost-effectiveness ratio [ICER] of $35 143 per life-year gained). The strategies of IHC + BRAF, germline testing and universal germline testing of colon cancer probands had ICERs of $144 117 and $996 878, respectively. CONCLUSIONS: This analysis suggests that the initial step in screening for Lynch Syndrome should be the use of predictive models in probands. Universal tumor testing and general population screening strategies are not cost-effective. When family history is unavailable, alternate strategies are appropriate. Documentation of family history and screening for Lynch Syndrome using a predictive model may be considered a quality-of-care measure for patients with colorectal cancer.

Ontology Driven Construction of a Knowledgebase for Bayesian Decision Models Based on UMLS.

All decision models use some form of language to describe domain elements and their interactions. The terminology is often specific and even unique to the algorithm and is a choice of designers. Nevertheless the domain elements and concepts of any decision problem are almost never unique and are used and reused in many other decision problems. The same is true about the information about those elements in the context of different decision problems. Put together, the information about any given element forms our knowledge about the element and if stored properly in a knowledgebase, can be used and reused as necessary without the need for duplication.In this paper we discuss creation of an ontology using UMLS vocabulary and semantic network that provides an abstract understanding of elements (or objects) in the problem domain. Based on this ontology, a knowledgebase will be constructed that provides further information about the object in relation to another object or objects as described in the semantic links.A knowledgebase structured as such will have the benefit of problem-independence. It can be expanded as needed to include other objects that are used in a different series of problems and therefore, will have a one to many mapping between knowledgebase and decision models. Updating the knowledgebase will update the decision models seamlessly and maintenance will be less of an issue across decision models and within the knowledgebase. We are using this approach in building Bayesian decision models using Bayesian networks; however, this approach is not limited to Bayesian networks and has been and can be used for other decision making purposes.