Zhaohui Zou

Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States in the current year and compiles the most recent data on cancer incidence, mortality, and survival. Incidence data were collected by the National Cancer Institute, the Centers for Disease Control and Prevention, and the North American Association of Central Cancer Registries and mortality data were collected by the National Center for Health Statistics. A total of 1,665,540 new cancer cases and 585,720 cancer deaths are projected to occur in the United States in 2014. During the most recent 5 years for which there are data (2006-2010), delay-adjusted cancer incidence rates declined slightly in men (by 0.6% per year) and were stable in women, while cancer death rates decreased by 1.8% per year in men and by 1.4% per year in women. The combined cancer death rate (deaths per 100,000 population) has been continuously declining for 2 decades, from a peak of 215.1 in 1991 to 171.8 in 2010. This 20% decline translates to the avoidance of approximately 1,340,400 cancer deaths (952,700 among men and 387,700 among women) during this time period. The magnitude of the decline in cancer death rates from 1991 to 2010 varies substantially by age, race, and sex, ranging from no decline among white women aged 80 years and older to a 55% decline among black men aged 40 years to 49 years. Notably, black men experienced the largest drop within every 10-year age group. Further progress can be accelerated by applying existing cancer control knowledge across all segments of the population.

The age-adjusted cancer rates are defined as the weighted average of the age-specific cancer rates, where the weights are positive, known, and normalized so that their sum is 1. Fay and Feuer developed a confidence interval for a single age-adjusted rate based on the gamma approximation. Fay used the gamma approximations to construct an F interval for the ratio of two age-adjusted rates. Modifications of the gamma and F intervals are proposed and a simulation study is carried out to show that these modified gamma and modified F intervals are more efficient than the gamma and F intervals, respectively, in the sense that the proposed intervals have empirical coverage probabilities less than or equal to their counterparts, and that they also retain the nominal level. The normal and beta confidence intervals for a single age-adjusted rate are also provided, but they are shown to be slightly liberal. Finally, for comparing two correlated age-adjusted rates, the confidence intervals for the difference and for the ratio of the two age-adjusted rates are derived incorporating the correlation between the two rates. The proposed gamma and F intervals and the normal intervals for the correlated age-adjusted rates are recommended to be implemented in the Surveillance, Epidemiology and End Results Program of the National Cancer Institute.

The annual percent change (APC) is often used to measure trends in disease and mortality rates, and a common estimator of this parameter uses a linear model on the log of the age-standardized rates. Under the assumption of linearity on the log scale, which is equivalent to a constant change assumption, APC can be equivalently defined in three ways as transformations of either (1) the slope of the line that runs through the log of each rate, (2) the ratio of the last rate to the first rate in the series, or (3) the geometric mean of the proportional changes in the rates over the series. When the constant change assumption fails then the first definition cannot be applied as is, while the second and third definitions unambiguously define the same parameter regardless of whether the assumption holds. We call this parameter the percent change annualized (PCA) and propose two new estimators of it. The first, the two-point estimator, uses only the first and last rates, assuming nothing about the rates in between. This estimator requires fewer assumptions and is asymptotically unbiased as the size of the population gets large, but has more variability since it uses no information from the middle rates. The second estimator is an adaptive one and equals the linear model estimator with a high probability when the rates are not significantly different from linear on the log scale, but includes fewer points if there are significant departures from that linearity. For the two-point estimator we can use confidence intervals previously developed for ratios of directly standardized rates. For the adaptive estimator, we show through simulation that the bootstrap confidence intervals give appropriate coverage.

BACKGROUND: Cervical cancer prevention programs are being reconfigured to incorporate human papillomavirus (HPV) testing and vaccination. To define priority areas for prevention efforts, we examined the geographic distribution of cervical cancer screening, incidence, stage, and mortality in the United States, prior to the introduction of HPV-based prevention technologies. METHODS: County-level cervical cancer incidence data from 37 central registries were obtained from Surveillance, Epidemiology, and End Results and North American Association of Central Cancer Registries. A spatial-temporal model that accounted for demographic and behavioral attributes was used to generate a complete view of county-level incidence from 1995 to 2004, including counties with missing data. Distribution of stage at diagnosis was examined by registry. Counties with high mortality and infrequent screening were identified using vital statistics and newly available county-level screening estimates. RESULTS: Compared with non-Hispanic whites and Asian and Pacific Islanders, incidence rates were higher among non-Hispanic black, American Indian and Alaska Native, and Hispanic women. Counties with infrequent screening often experienced elevated incidence and mortality rates and were located in states with suboptimal stage at diagnosis profiles. Affected areas included Appalachia, the southeastern Atlantic states, and the lower Mississippi Valley. Elevated death rates were experienced in central counties of large metropolitan areas. CONCLUSIONS: Geographic and racial/ethnic variability were evident in cervical cancer incidence and mortality. Women living in areas with endemic poverty would benefit from access to HPV-based prevention technologies. IMPACT: These findings provide a baseline for monitoring progress in cervical cancer control in the era of HPV-based prevention.

BACKGROUND: Intrahepatic (ICC) and extrahepatic cholangiocarcinomas (ECC) are tumors that arise from cholangiocytes in the bile duct, but ICCs are coded as primary liver cancers while ECCs are coded as biliary tract cancers. The etiology of these tumors is not well understood. It has been suggested that the etiology of ICC is more similar to that of another type of liver cancer, hepatocellular carcinoma (HCC), than to the etiology of ECC. If this is true, geographic incidence patterns and trends in ICC incidence should be more similar to that of HCC than ECC. METHODS: To examine this hypothesis, data from the North American Association of Central Cancer Registries Cancer in North America data file were analyzed. Incidence rates and joinpoint trends were calculated by demographic subgroup. County-level incidence rates were mapped. RESULTS: Overall incidence rates, racial distribution, male:female ratio, and peak ages were more similar between ICC and ECC than with HCC. During 2000-2009, average annual incidence rates of ECC increased. During 2005-2009, average annual ICC incidence rates also increased. High rates for all three cancer sites were found in the Pacific region, particularly Hawaii and Alaska. Rates of ICC and ECC were also high in the Northeast and the upper Midwest, while rates of HCC were high in the South. CONCLUSIONS: Demographic patterns and geographical variation were more closely related between ICC and ECC than HCC, suggesting that the etiology of ICC and ECC may be similar. Increasing rates of both tumors suggest that further etiology studies are warranted.