Optimal Timing of Radiotherapy Following Gross Total or Subtotal Resection of Glioblastoma: A Real-World Assessment using the National Cancer Database.

Treatment for glioblastoma (GBM) includes surgical resection and adjuvant radiotherapy (RT) and chemotherapy. The optimal time interval between surgery and RT remains unclear. The National Cancer Database (NCDB) was queried for patients with GBM. Overall survival (OS) was estimated using Kaplan-Meier and log-rank tests. Univariate (UVA) and multivariable Cox regression (MVA) modeling was used to determine predictors of OS. A total of 45,942 patients were included. On MVA: younger age, female gender, black ethnicity, higher KPS, obtaining a gross total resection (GTR), MGMT promoter-methylated gene status, unifocal disease, higher RT dose, and RT delay of 4-8 weeks had improved OS. Patients who underwent a subtotal resection (STR) had worsened survival with RT delay ≤4 weeks and patients with GTR had worsened survival when RT was delayed >8 weeks. This analysis suggests that an interval of 4-8 weeks between resection and RT results in better survival. Delays >8 weeks in patients with a GTR and delays <4 weeks in patients with a STR/biopsy resulted in worse survival. This impact of time delay from surgery to RT, in conjunction with extent of resection, should be considered in the clinical management of patients and future designs of clinical trials.

Volumetric assessment of apparent diffusion coefficient predicts outcome following chemoradiation for cervical cancer.

OBJECTIVE: To determine the utility of volumetric diffusion weighted imaging (DWI) compared to other clinical factors for predicting recurrence and survival in cervical cancer patients treated with definitive chemoradiation. METHODS AND MATERIALS: We retrospectively studied cervical cancer patients treated with definitive chemoradiation between 2009-2013 at a single institution with a baseline MRI with DWI and 18F-FDG positron emission tomography/computed tomography (FDG-PET) scan. To identify clinical and imaging metrics correlated with survival and recurrence endpoints, variable importance values were calculated from random forest models. To provide clinically relevant threshold values, recursive partitioning analysis dichotomized patients into potential risk groups based on selected metrics. Cox's proportional hazard models assessed the effect of clinical and imaging factors on survival endpoints. RESULTS: Ninety-three patients were included in the analysis (median age 50 years). At a median follow-up of 35.6 months, 32 patients (34%) had disease recurrence. In the best multivariate model including clinical and imaging parameters, 90th percentile ADC < 1.917 was the only significantly associated factor with worse progression free survival (PFS). Overall survival, PFS, and distant metastasis free survival (DMFS) were significantly different between patient groups divided on 90th percentile ADC with threshold of 1.917 × 10-3 mm2/s and MRI volume with threshold of 18.9 cc (P = 0.037, P = 0.0002, P = 0.001). High MRI volume and low ADC were associated with worse clinical outcomes. CONCLUSIONS: Volumetric 90th percentile ADC value of the primary tumor on pretreatment MRI was a significant predictor of PFS and DMFS in cervical cancer patients, independent of established clinical factors and SUV on FDG-PET.

Addition of Definitive Radiotherapy to Chemotherapy in Patients With Newly Diagnosed Metastatic Nasopharyngeal Cancer.

Background: Management of metastatic (M1) nasopharyngeal cancer (NPC) is controversial; data suggest high overall survival (OS) rates with definitive chemoradiotherapy (CRT). Herein, we evaluated OS in patients with M1 NPC undergoing chemotherapy alone versus CRT. Methods: The National Cancer Data Base was queried for M1 NPC cases. Patients undergoing no/unknown chemotherapy and/or with unknown/nondefinitive radiotherapy (RT) doses (<60 Gy) were excluded. Logistic regression analysis ascertained clinical factors associated with RT administration. Kaplan-Meier analysis evaluated OS between both cohorts; Cox proportional hazards modeling assessed factors associated with OS. Survival was then evaluated between matched populations using inverse-probability-weighted regression adjustment. OS between groups was also measured in patients surviving ≥1 and ≥3 years to address bias from poor-prognostic subsets (eg, widely disseminated disease), and those receiving CRT ≤30 and ≤60 days of each other (surrogates for concurrent CRT) versus >30 and >60 days (sequential) of each other. Results: Of 555 patients, 296 (53%) received chemotherapy alone and 259 (47%) underwent CRT. Patients undergoing CRT more often had private insurance (P=.001) and lived in areas with higher education levels (P=.028). Median OS in the chemotherapy-only and CRT cohorts were 13.7 and 25.8 months, respectively (P<.001); differences persisted between matched populations (P<.001). On multivariate analysis, receipt of additional RT independently predicted for improved OS (P<.001). OS differences between cohorts remained apparent when evaluating patients surviving for ≥1 (P<.001) and ≥3 (P=.002) years. Patients who received concurrent or sequential CRT displayed improved OS over those receiving chemotherapy alone, for both the 30-day (P<.001) and 60-day cutoffs (P<.001). Conclusions: Patients with M1 NPC undergoing definitive RT and chemotherapy experienced higher survival than those receiving chemotherapy alone. Risk stratification and patient selection for such combined modality interventions is critical.

Insurance Status and Racial Disparities in Cancer-Specific Mortality in the United States: A Population-Based Analysis.

Background: Cancer-specific mortality (CSM) is known to be higher among blacks and lower among Hispanics compared with whites. Private insurance confers CSM benefit, but few studies have examined the relationship between insurance status and racial disparities. We sought to determine differences in CSM between races within insurance subgroups.Methods: A population-based cohort of 577,716 patients age 18 to 64 years diagnosed with one of the 10 solid malignancies causing the greatest mortality over 2007 to 2012 were obtained from Surveillance, Epidemiology, and End Results. A Cox proportional hazards model for CSM was constructed to adjust for known prognostic factors, and interaction analysis between race and insurance was performed to generate stratum-specific HRs.Results: Blacks had similar CSM to whites among the uninsured [HR = 1.01; 95% confidence interval (CI), 0.96-1.05], but higher CSM among the Medicaid (HR = 1.04; 95% CI, 0.01-1.07) and non-Medicaid (HR = 1.14; 95% CI, 1.12-1.16) strata. Hispanics had lower CSM compared with whites among uninsured (HR = 0.80; 95% CI, 0.76-0.85) and Medicaid (HR = 0.88; 95% CI, 0.85-0.91) patients, but there was no difference among non-Medicaid patients (HR = 0.99; 95% CI, 0.97-1.01). Asians had lower CSM compared with whites among all insurance types: uninsured (HR = 0.80; 95% CI, 0.76-0.85), Medicaid (HR = 0.81; 95% CI, 0.77-0.85), and non-Medicaid (HR = 0.85; 95% CI, 0.83-0.87).Conclusions: The disparity between blacks and whites was largest, and the advantage of Hispanic race was absent within the non-Medicaid subgroup.Impact: These findings suggest that whites derive greater benefit from private insurance than blacks and Hispanics. Further research is necessary to determine why this differential exists and how disparities can be improved. Cancer Epidemiol Biomarkers Prev; 26(6); 869-75. ©2017 AACR.

Impact of Insurance Status on Radiation Treatment Modality Selection Among Potential Candidates for Prostate, Breast, or Gynecologic Brachytherapy.

PURPOSE: The Patient Protection and Affordable Care Act looks to expand both private and Medicaid insurance. To evaluate how these changes may affect the field of radiation oncology, we evaluated the association of insurance status with the use of brachytherapy in cancers for which this treatment technique is used. METHODS AND MATERIALS: A total of 190,467 patients met the inclusion criteria, of whom 95,292 (50.0%) had breast cancer, 61,096 (32.1%) had prostate cancer, 28,194 (14.8%) had endometrial cancer, and 5885 (3.1%) had cervical cancer. A multivariate logistic regression model was used to determine the association between insurance status and receipt of brachytherapy among patients treated definitively for prostate and cervical cancer or postoperatively for breast and endometrial cancer. RESULTS: The rates of non-Medicaid insurance were 49.9% (cervical), 85.3% (endometrial), 87.4% (breast), and 90.9% (prostate) (P<.001). In a logistic regression, patients who received radiation therapy were less likely to receive brachytherapy if they had Medicaid coverage (odds ratio [OR] 0.57, 95% confidence interval [CI] 0.53-0.61, P<.001) or did not have insurance coverage (OR 0.50, 95% CI 0.45-0.56, P<.001) compared with those with non-Medicaid insurance. On subset analysis, patients with Medicaid coverage or without insurance coverage were significantly less likely to receive brachytherapy than were those with non-Medicaid insurance for all 4 sites, except for patients with endometrial cancer. CONCLUSIONS: Despite being a cost-effective treatment modality, brachytherapy is less often used in the definitive or postoperative management of cancer in patients with Medicaid coverage or without insurance. Upcoming health policy changes resulting in the expansion of private insurance and Medicaid will likely increase access to and demand for brachytherapy.

Variation in insurance status by patient demographics and tumor site among nonelderly adult patients with cancer.

BACKGROUND: In the United States, an estimated 48 million individuals live without health insurance. The purpose of the current study was to explore the Variation in insurance status by patient demographics and tumor site among nonelderly adult patients with cancer. METHODS: A total of 688,794 patients aged 18 to 64 years who were diagnosed with one of the top 25 incident cancers (representing 95% of all cancer diagnoses) between 2007 and 2010 in the Surveillance, Epidemiology, and End Results (SEER) database were analyzed. Patient characteristics included age, race, sex, marital status, and rural or urban residence. County-level demographics included percent poverty level. Insurance status was defined as having non-Medicaid insurance, Medicaid coverage, or no insurance. RESULTS: On multivariate logistic regression analyses, younger age, male sex, nonwhite race, being unmarried, residence in counties with higher levels of poverty, and rural residence were associated with being uninsured versus having non-Medicaid insurance (all P <.001). The highest rates of non-Medicaid insurance were noted among patients with prostate cancer (92.3%), melanoma of the skin (92.5%), and thyroid cancer (89.5%), whereas the lowest rates of non-Medicaid insurance were observed among patients with cervical cancer (64.2%), liver cancer (67.9%), and stomach cancer (70.9%) (P <.001). Among uninsured individuals, the most prevalent cancers were lung cancer (14.9%), colorectal cancer (12.1%), and breast cancer (10.2%) (P <.001). Lung cancer caused the majority of cancer mortality in all insurance groups. CONCLUSIONS: Rates of insurance coverage vary greatly by demographics and by cancer type. The expansion of health insurance coverage would be expected to disproportionally benefit certain demographic populations and cancer types.

Disparities in stage at diagnosis, treatment, and survival in nonelderly adult patients with cancer according to insurance status.

PURPOSE: The purpose of this study was to determine the association of insurance status with disease stage at presentation, treatment, and survival among the top 10 most deadly cancers using the SEER database. PATIENTS AND METHODS: A total of 473,722 patients age 18 to 64 years who were diagnosed with one of the 10 most deadly cancers in the SEER database from 2007 to 2010 were analyzed. A Cox proportional hazards model was used for multivariable analyses to assess the effect of patient and tumor characteristics on cause-specific death. RESULTS: Overall, patients with non-Medicaid insurance were less likely to present with distant disease (16.9%) than those with Medicaid coverage (29.1%) or without insurance coverage (34.7%; P < .001). Patients with non-Medicaid insurance were more likely to receive cancer-directed surgery and/or radiation therapy (79.6%) compared with those with Medicaid coverage (67.9%) or without insurance coverage (62.1%; P < .001). In a Cox regression that adjusted for age, race, sex, marital status, residence, percent of county below federal poverty level, site, stage, and receipt of cancer-directed surgery and/or radiation therapy, patients were more likely to die as a result of their disease if they had Medicaid coverage (hazard ratio [HR], 1.44; 95% CI, 1.41 to 1.47; P < .001) or no insurance (HR, 1.47; 95% CI, 1.42 to 1.51; P < .001) compared with non-Medicaid insurance. CONCLUSION: Among patients with the 10 most deadly cancers, those with Medicaid coverage or without insurance were more likely to present with advanced disease, were less likely to receive cancer-directed surgery and/or radiation therapy, and experienced worse survival.

Validation of Recursive Partitioning Analysis and Diagnosis-Specific Graded Prognostic Assessment in patients treated initially with radiosurgery alone.

OBJECT: Brain metastases present a therapeutic challenge because patients with metastatic cancers live longer now than in the recent past due to systemic therapies that, while effective, may not penetrate the blood-brain barrier. In the present study the authors sought to validate the Diagnosis-Specific Graded Prognostic Assessment (DS-GPA), a new prognostic index that takes into account the histological characteristics of the primary tumor, and the Radiation Therapy Ontology Group Recursive Partitioning Analysis (RPA) system by using a single-institution database of patients who were treated initially with stereotactic radiosurgery (SRS) alone for brain metastases. METHODS: Investigators retrospectively identified adult patients who had undergone SRS at a single institution, MD Anderson Cancer Center, for initial treatment of brain metastases between 2003 and 2010 but excluded those who had undergone craniotomy and/or whole-brain radiation therapy at an earlier time; the final number was 251. The Leksell Gamma Knife was used to treat 223 patients, and a linear accelerator was used to treat 28 patients. The patient population was grouped according to DS-GPA scores as follows: 0-0.5 (7 patients), 1 (33 patients), 1.5 (25 patients), 2 (63 patients), 2.5 (14 patients), 3 (68 patients), and 3.5-4 (41 patients). The same patients were also grouped according to RPA classes: 1 (24 patients), 2 (216 patients), and 3 (11 patients). The most common histological diagnoses were non-small cell lung cancer (34%), melanoma (29%), and breast carcinoma (16%). The median number of lesions was 2 (range 1-9) and the median total tumor volume was 0.9 cm(3) (range 0.3-22.9 cm(3)). The median radiation dose was 20 Gy (range 14-24 Gy). Stereotactic radiosurgery was performed as the sole treatment (62% of patients) or combined with a salvage treatment consisting of SRS (22%), whole-brain radiation therapy (12%), or resection (4%). The median duration of follow-up was 9.4 months. RESULTS: In this patient group the median overall survival was 11.1 months. The DS-GPA prognostic index divided patients into prognostically significant groups. Median survival times were 2.8 months for DS-GPA Scores 0-0.5, 3.9 months for Score 1, 6.6 months for Score 1.5, 12.9 months for Score 2, 11.9 months for Score 2.5, 12.2 months for Score 3, and 31.4 months for Scores 3.5-4 (p < 0.0001). In the RPA groups, the median overall survival times were 38.8 months for Class 1, 9.4 months for Class 2, and 2.8 months for Class 3 (p < 0.0001). Neither the RPA class nor the DS-GPA score was prognostic for local tumor control or new lesion-free survival. A multivariate analysis revealed that patient age > 60 years, Karnofsky Performance Scale score ≤ 80%, and total lesion volume > 2 cm(3) were significant adverse prognostic factors for overall survival. CONCLUSIONS: Application of the DS-GPA to a database of patients with brain metastases who were treated with SRS appears to be valid and offers additional prognostic refinement over that provided by the RPA. The DS-GPA may also allow for improved selection of patients to undergo initial SRS alone and should be studied further.