Academic Cancer Programs Research Articles

National Trends and Predictors of Androgen Deprivation Therapy Use in Low-Risk Prostate Cancer

Androgen deprivation therapy (ADT) is not recommended for low-risk prostate cancer because of its lack of benefit and potential for harm. We evaluated the incidence and predictors of ADT use in low-risk disease. Using the National Cancer Database, we identified 197,957 patients with low-risk prostate cancer (Gleason score of 3+3=6, prostate-specific antigen level <10ng/mL, and cT1-T2a) diagnosed from 2004 to 2012 with complete demographic and treatment information.We used multiple logistic regression to evaluate predictors of ADT use and Cox regression to examine its association with all-cause mortality. Overall ADT use decreased from 17.6% in 2004 to 3.5% in 2012. In 2012, 11.5% of low-risk brachytherapy patients and 7.6% of external beam radiation therapy patients received ADT. Among 82,352 irradiation-managed patients, predictors of ADT use included treatment in a community versus academic cancer program (adjusted odds ratio [AOR], 1.60; 95% confidence interval [CI], 1.50-1.71; P<.001; incidence, 14.0% vs 6.0% in 2012); treatment in the South (AOR, 1.51), Midwest (AOR, 1.81), or Northeast (AOR, 1.90) versus West (P<.001); and brachytherapy use versus external beam radiation therapy (AOR, 1.32; 95% CI, 1.27-1.37; P<.001). Among 25,196 patients who did not receive local therapy, predictors of primary ADT use included a Charlson-Deyo comorbidity score of ≥2 versus 0 (AOR, 1.42; 95% CI, 1.06-1.91; P=.018); treatment in a community versus academic cancer program (AOR, 1.61; 95% CI, 1.37-1.90; P<.001); and treatment in the South (AOR, 1.26), Midwest (AOR, 1.52), or Northeast (AOR, 1.28) versus West (P≤.008). Primary ADT use was associated with increased all-cause mortality in patients who did not receive local therapy (adjusted hazard ratio, 1.28; 95% CI, 1.14-1.43; P<.001) after adjustment for age and comorbidity. ADT use in low-risk prostate cancer has declined nationally but may remain an issue of concern in certain populations and regions.

Impact of Facility Type and Surgical Volume on 10-Year Survival in Patients Undergoing Hepatic Resection for Hepatocellular Carcinoma

Previous studies have demonstrated improved in-hospital mortality after hepatic resection for hepatocellular carcinoma (HCC) at teaching hospitals. The objective of this study was to evaluate if resection of HCC at academic cancer programs (ACP) is associated with improved 10-year survival. Using the National Cancer Data Base (NCDB) (1998 to 2011), we evaluated patients undergoing hepatic resection for HCC at ACPs, comprehensive community cancer programs (CCCPs), and community cancer programs (CCPs). High volume cancer programs (HVCPs) were defined as performing 10 or more hepatectomies per year. Multivariate Cox proportional hazard models by stepwise selection were applied to estimate hazard ratios (HR) of predictors of survival. The Kaplan-Meier method was used to generate survival curves at each facility type, and survival rates were compared using the log-rank test. We identified 12,757 patients undergoing hepatic resection for HCC at ACPs (n= 8,404), CCPs (n= 483), and CCCPs (n= 3,870). Sixty-two percent (n= 5,191) of patients treated at ACPs were at high volume institutions compared with 11.6% (n= 446) and 0% of CCCPs and CCPs, respectively (p < 0.0001). On multivariable analysis, patients undergoing hepatic resection at transplant centers (p < 0.0001) and HVCPs had significantly improved survival (p < 0.0001). Adjusted 10-year survival rates were 28.7% at high volume ACPs, 28.2% at high volume CCCPs, 24.9% at low volume CCCPs, 25.1% at low volume ACPs, and 21.3% at CCPs (p ≤ 0.0001). Patients undergoing hepatic resection for HCC at HVCPs had a significantly improved 10-year survival. Regionalization of HCC treatment to HVCPs may improve long-term survival.

Survival as a measure of quality of cancer care and advances in therapy: Lessons learned from analyses of the National Cancer Data Base (NCDB).

173 Background: Many quality metrics of cancer care are process measures, based on whether a patient received recommended treatment for diagnosis and stage of their disease. Survival is dependent on patient characteristics, disease specifics, and care received (surgery, systemic therapies, radiation). Some argue survival is the ultimate measure of cancer care quality. Survival calculated from registry data may be a better indication of the real effects of new therapies as it contains a broad representation of patients who may not meet the eligibility criteria for clinical trials. Methods: The NCDB is composed of registry data from approximately 1,500 hospital based cancer programs, and includes stage, demographic data, co-morbidities, treatments, and vital status. Survival analyses were derived from NCDB data for all stages of breast cancer, non-small cell lung cancer (NSCLC), and pancreatic cancer. These diseases were selected because breast cancer has a high survival rate, whereas NSCLC and pancreatic cancer are diseases with a poor prognosis, but recent advances may have improved survival. Un-adjusted and risk adjusted survival were analyzed by socioeconomic, tumor, and hospital factors including stage, comorbidities, diagnosis year (to assess new treatment trends), and type of institution (academic, comprehensive community, and community cancer programs). Results: Results for these diseases and variables noted will be presented. Whereas better un-adjusted survival rates were often seen at academic cancer programs, differences disappeared after risk-adjustment. Improved survival was seen in more recent years, probably representing new treatment effects, though gains were modest and stage dependent. Conclusions: Measuring survival across hospitals and regions is critical to understanding the state of cancer treatment nationally and the effect of quality and therapy advances on patients across a variety of clinical settings. Methodologic challenges in analyzing and interpreting survival data must be realized, and continued innovation in the collection and analysis of data is needed.

Impact of the Type of Treatment Facility on the Outcome of Acute Myeloid Leukemia in the Adolescents and Young Adults: A National Cancer Data Base (NCDB) Study from 2003-2011

Background: Unlike acute lymphoblastic leukemia, data on acute myelogenous leukemia (AML) in the adolescents and young adults (AYA) are limited and generally derived from clinical trials, which are mostly conducted in academic centers. It is unclear whether the choice of treatment facility influences clinical outcome independent of disease biology and socio-demographic factors. This study used the National Cancer Data Base, a nationwide oncology database covering 70% of the US cancer population, to address this question.Methods: We identified 11,712 AYA patients who were diagnosed with AML from 2003-2011. We excluded patients who were: a) 15-17 years of age (n = 3,104) as treatment facility data were not available for age <18 years; b) not treated at the reporting facilities (n = 415) as follow-up might be incomplete; c) treated at treatment facilities with ≤100 new cancer cases/year (n = 18); and d) those without follow-up data (n = 47). Treatment facilities were classified as academic, comprehensive community (>500 new cancer cases/year), or community (101-500 new cancer cases/year) cancer programs. AMLs harboring t(15;17), inv(16), or t(8;21) were defined as good-risk, while the rest were considered non-good risk. Overall survival from the time of AML diagnosis was the primary outcome. We used multivariate imputation by chained equation to impute missing values, weighted Cox regression to obtain average hazard ratios (HRs), and pooled Wald c2 statistics to detect interaction.Results: We included 8,128 AYA patients with AML in the study and 25.2% were good risk. Among the good risk AMLs, 11.6%, 12.3%, and 76.1% had t(8;21), inv16, and t(15;17), respectively. The distribution of patients by treatment facility were academic (64.1%), comprehensive community (32.9%), and community (3.0%). After detecting an interaction between AML risk and type of treatment facility (P=0.038), we stratified treatment facility by AML risk and found significant differences in overall survival among good risk (P=0.02) but not non-good risk AML (P=0.19). This survival difference persisted even after adjusting for demographic (age, sex, race/ethnicity), socioeconomic (income, education, medical insurance), geographic (area of residence, travel distance), co-morbidities (Charlson-Deyo score), and treatment (receipt of chemotherapy) factors. Patients with good risk AML treated in comprehensive community cancer programs had a higher risk of death compared to those treated in academic programs (adjusted HR: 1.41, 95% CI: 1.11-1.79). For community cancer programs, the risk of death was also higher but did not reach statistical significance (adjusted HR: 1.22, 95% CI: 0.68-2.21). ). Subset analysis showed that the survival difference among those with good risk AML was observed in t(15;17) or acute promyelocytic leukemia (APL; P=0.02) but not in t(8;21) or inv16 (P=0.79). The disparity occurred primarily during the first month of APL diagnosis, wherein the risk of death was two-fold higher in community programs (Figure).Conclusions: Among AYA patients with AML, treatment at academic cancer programs was associated with a better survival, but only for the APL subgroup. Because APL comprises a fifth of all AMLs in the AYA and is a highly curable cancer, health care delivery research in APL should become a priority in this age group. [Display omitted] DisclosuresAl-Kali:Celgene: Research Funding.

Disparities in the Use of Breast-Conserving Therapy Among Patients With Early-Stage Breast Cancer.

Although breast-conserving therapy (BCT) is an accepted modality for treatment of early-stage breast cancer, many women continue to undergo mastectomy. Detailing the factors associated with choice of BCT may assist with overcoming barriers in the use of this treatment modality. To conduct a population-based examination of the factors that influence the use of BCT. Using the National Cancer Data Base, we examined the surgical choices of women with stage T1 or T2 breast cancer treated between 1998 and 2011. Logistic regression analysis conducted between September 19, 2013, and August 26, 2014, was used to assess the multivariate association between patient and facility variables and the probability of undergoing BCT. Factors associated with the use of BCT. A cohort of 727,927 women was identified in the National Cancer Data Base. Use of BCT, determined using odds ratio (OR) and 95% CI, was greater in patients aged 52 to 61 years compared with younger patients (1.14; 1.12-1.15) and in those with the highest educational level (1.16; 1.14-1.19). Rates of BCT were lower in patients without insurance compared with those with private insurance (0.75; 0.72-0.78) and in those with the lowest median income (0.92; 0.90-0.94). Academic cancer programs, US Northeast location, and residence within 27.8 km of a treatment facility were associated with greater BCT rates than were community cancer programs (1.13; 1.11-1.15), Southern location (1.50; 1.48-1.52), and residence farther from a treatment facility (1.25; 1.23-1.27). When comparing BCT use in 1998 with use in 2011, increases were seen across age groups (from 48.2% to 59.7%), in community cancer programs (48.4% in 1998 vs 58.8% in 2011), and in facilities located in the South (45.1% in 1998 vs 55.3% in 2011). Although the use of BCT has increased during the past 14 years, nonclinical factors, including socioeconomic demographics, insurance, and travel distance to the treatment facility, persist as key barriers to receipt of BCT. Interventions that address these barriers may facilitate further uptake of BCT.

Disparities in utilization of breast-conserving therapy among breast cancer patients.

104 Background: Since 1990 breast conserving therapy (BCT) has become a widely accepted modality in the treatment of breast cancer. However, many women continue to undergo mastectomy over BCT. The objective of this study was to provide a comprehensive population based review of the factors that influence utilization of BCT. Methods: Using the National Cancer Database (NCDB), we evaluated women who underwent a mastectomy or BCT for T1/T2, any N breast cancer between 1998 and 2011. We conducted a retrospective review of patient and facility variables associated with undergoing BCT and the trends over time. Logistic regression analysis was used to assess the multivariate relationship between these variables and the probability of undergoing BCT. Results: Among the 727,927 patients who met study criteria, BCT rates increased from 54% in 1998 to 59% in 2006 and then stabilized. After adjusting for demographic and clinical characteristics, BCT utilization was more likely in patients aged 52-61 compared to younger patients (odds ratio (OR) 1.14 {95% CI 1.12-1.15}) and in those with the highest education level (OR 1.16 {95% CI 1.14-1.19}). BCT rates were higher in patients with private insurance compared to the uninsured (OR 1.33 {95% CI 1.28-1.38}) and in those with the highest median income (OR 1.09 {95% CI 1.06-1.11}) (all p &lt; 0.0001). Academic Cancer Programs, facilities in the Northeast and patients who lived within 17 miles of a treatment facility had higher utilization of BCT than Community Cancer Programs (OR 1.13 {95% CI 1.11-1.15}), facilities located in the South (OR 1.50 {95% CI 1.48-1.52}) and those who lived further from a treatment facility (OR 1.25 {95% CI 1.23-1.27}) (all p&lt;0.0001). When comparing BCT utilization in 1998 and 2011, increases were seen across age groups, in community cancer programs and in facilities located in the South; however, disparities by insurance status, income level and travel greater than 17 miles to a treatment facility persist. Conclusions: BCT rates have increased during the last two decades. Disparities based on age, geographic location and type of cancer program have improved. However, socio-economic status and travel distance to treatment facilities persist as key barriers to BCT utilization.