Objective To evaluate 30-day and 90-day mortality after major pulmonary resection for lung cancer including the relationship to hospital volume. Methods Major lung resections from 2007 to 2011 were ...identified in the National Cancer Data Base. Mortality was compared according to annual volume and demographic and clinical covariates using univariate and multivariable analyses, and included information on comorbidity. Statistical significance ( P < .05) and 95% confidence intervals were assessed. Results There were 124,418 major pulmonary resections identified in 1233 facilities. The 30-day mortality rate was 2.8%. The 90-day mortality rate was 5.4%. Hospital volume was significantly associated with 30-day mortality, with a mortality rate of 3.7% for volumes less than 10, and 1.7% for volumes of 90 or more. Other variables significantly associated with 30-day mortality include older age, male sex, higher stage, pneumonectomy, a previous primary cancer, and multiple comorbidities. Similar results were found for 90-day mortality rates. In the multivariate analysis, hospital volume remained significant with adjusted odds ratios of 2.1 (95% confidence interval CI, 1.7-2.6) for 30-day mortality and 1.3 (95% CI, 1.1-1.6) for conditional 90-day mortality for the hospitals with the lowest volume (<10) compared with those with the highest volume (>90). Hospitals with a volume less than 30 had an adjusted odds ratio for 30-day mortality of 1.3 (95% CI, 1.2-1.5) compared with those with a volume greater than 30. Conclusions Mortality at 30 and 90 days and hospital volume should be monitored by institutions performing major pulmonary resection and benchmarked against hospitals performing at least 30 resections per year.
Background Although strong volume-outcome relationships exist for many cancer operations, patients continue to undergo these operations at low-volume hospitals. Methods Patients were identified from ...the National Cancer Data Base from 2010–2013 who underwent resection for bladder, breast, esophagus, lung, pancreas, rectum, and stomach cancers. Low-volume hospitals were defined as those in the bottom quartile by surgical volume for each cancer type separately. Logistic regression models were constructed to assess patient-level factors associated with undergoing cancer surgery at low-volume hospitals across cancer types while controlling for tumor characteristics. Survival outcomes (30- and 90-day mortality; overall survival) were also assessed. Results Low volume thresholds were 4, 84, 4, 18, 8, 7, and 4 resections per year for bladder, breast, esophagus, lung, pancreas, rectum, and stomach cancers, respectively, resulting in 772 (74.1%), 828 (57.5%), 664 (77.5%), 830 (64.7%), 716 (79.2%), 898 (65.1%), and 888 (68.5%) hospitals classified as low-volume hospitals, respectively. For all the cancers examined, patients were more likely to undergo operation at low-volume hospitals if they traveled shorter distances (home to surgical facility), resided in rural locations, or had not received neoadjuvant therapy. Other patient and tumor factors were not associated consistently with undergoing operation at low-volume hospitals. Patients who went to low-volume hospitals had poorer outcomes among the studied cancers. Conclusion Patients continue to undergo operation at low-volume hospitals due to where they live and how far they have to travel. Regionalization policy initiatives will remain challenging in this population. Efforts should therefore continue to emphasize quality improvement locally at each facility caring for patients with cancer.
Background Evaluating and improving the quality of cancer care requires complete information on cancer stage and treatment. Hospital-based registries are a key tool in this effort, but reports in the ...1990s showed that they fail to identify a major fraction of outpatient-administered treatment, including chemotherapy, endocrine therapy, and radiation. This can limit their value for evaluating patterns and quality of care. To determine the completeness of registry data in more recent years, we linked administrative claims from 2 private payers in Ohio to the National Cancer Data Base and Ohio Cancer Incidence and Surveillance System. Methods Incident breast and colorectal cancers among Ohio residents diagnosed in 2004–2006 were identified from linkage of the National Cancer Data Base, Ohio Cancer Incidence and Surveillance System, and payer insurance claims using ICD-9 and CPT procedure codes, and ICD-9 diagnosis codes. Linkage was accomplished using patient demographics, surgery dates, and hospital facility. Treatment found in claims and registry data were compared and assessed using the κ statistic. Results The analytic cohort included 2,552 breast and 822 colorectal cases. Results showed high agreement for breast surgery type, and moderately high agreement for colorectal surgery type. For breast cases, the registries captured 87% of chemotherapy, 86% of radiation, and 64% of endocrine treatment in claims. For colorectal cases, the registry captured 83% of chemotherapy and 84% of radiation in claims. Conclusions Hospital-based registries for breast and colon cancer diagnosed in 2004–2006 captured about 85% of radiation and chemotherapy data compared with claims data, a higher percentage than earlier reports. These findings provide direction and a cautionary note to those using registry data for study of patterns and quality of systemic and radiation therapy care.
Background Current American Joint Committee on Cancer/International Union against Cancer (AJCC/UICC) and European Network for the Study of Adrenal Tumors staging for adrenocortical carcinoma (ACC) ...have not shown a survival difference between patients with stage I/II disease. This study evaluates current staging systems for survival prediction using a larger cohort and assesses whether incorporating age into ACC staging improves survival predictions. Methods Patients in the National Cancer Data Base (1985–2006) with a diagnosis of ACC were identified and staged using a novel TNM-A staging system: Stage I (T1/T2N0M0, age ≤55), stage II (T1/T2N0M0, age >55), stage III (T1/T2N1M0 or T3/T4N0-N1M0, any age), or stage IV (any T any NM1, any age). Differences in overall survival (OS) by stage were compared using a Cox proportional hazards model. Results Staging was derived for 1,579 of 3,262 patients. Median age was 54 years; mean tumor size was 11.6 cm. Using current staging, differences in 5-year OS was observed only between patients with stages II/III and III/IV ACC. With TNM-A staging, differences in 5-year OS between all stages was significant (I/II P < .003, II/III P < .0001, III/IV P < .0001). Conclusion A staging system that incorporates patient age better predicts 5-year OS among patients with stages I/II ACC. Consideration should be given to including age in staging for ACC, because it may better inform providers about treatment and prognosis.
Purpose The proportion of renal cell carcinoma cases diagnosed at stage I is known to be increasing significantly. We characterized stage I tumors further in terms of tumor size at diagnosis using a ...large national cancer registry. Materials and Methods The National Cancer Data Base captures approximately 75% of all newly diagnosed cancer cases in the United States. The database was queried for all adults who were diagnosed between 1993 and 2004 with stage I renal cell carcinoma. Trends were assessed in mean size with time as well as in the proportion of stage I tumors diagnosed at less than 2.0, less than 2.5 and less than 3.0 cm. Results There were 104,150 patients in the National Cancer Data Base diagnosed with stage I renal cell carcinoma during the study period. A total of 10,279 stage I tumors (9.9%) were less than 2.0 cm, 26,621 (25.6%) were 2.5 cm or less and 39,879 (38.3%) were 3.0 cm or less. Analysis of stage I renal cell carcinoma diagnoses with time demonstrated a statistically significant increase in the proportion of renal masses 3.0 cm or less between 1993 and 2004 (32.5% vs 43.4%). Of tumors 3.0 cm or less the proportion smaller than 2.0 cm increased significantly during the study period from 24.1% in 1993 to 29.4% in 2004. Mean tumor size decreased from 4.1 to 3.6 cm between 1993 and 2004 (p <0.001). Conclusions Tumor size at diagnosis is decreasing with time in patients with stage I renal cell carcinoma. These data likely underestimate the proportion of all enhancing renal masses diagnosed at a small size. Patients with small masses may be appropriate candidates for nephron sparing surgery, energy based ablative therapy or active surveillance. Better technologies are needed to determine the diagnosis and prognosis of small enhancing renal masses.
Background
The National Cancer Database (NCDB) is a hospital-based cancer registry that includes diagnostic, staging, treatment, and outcomes data for newly diagnosed cancer patients in the United ...States. The NCDB data include 31 million records for patients diagnosed between 1985–2015. A Participant User File based on a subset of these data has been available to researchers at facilities accredited by the Commission on Cancer since 2010. This study aimed to compare the number of incident cancer cases in the NCDB with a national population cancer registry.
Methods
Incident cancer cases in the NCDB in 2012–2014 were compared with the number of cancer cases in the United States Cancer Statistics data for the 2012–2014 diagnosis years. Comparisons were made by primary site and other factors.
Results
In 2012–2014, the NCDB captured 72% of the cancer cases in the United States, which was slightly higher than the 67% and 69% reported respectively in two prior assessments. Among the top 10 major cancer sites, the highest coverage (80%) was found for breast cancer, and the lowest was found for melanoma of the skin (52%) and prostate (58%). Colon, bladder, and kidney and renal pelvis cancers had relatively high coverage of 71%, 70% and 78%, respectively, whereas lung and bronchus had slightly lower coverage (65%).
Conclusions
The NCDB coverage of U.S. cancer cases has remained relatively high (72%), but differences remain by cancer site and other factors that should be taken into account by users of the NCDB data.
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