Prediction of Risk of Metastatic Recurrence for Female Breast Cancer Patients in the Presence of Competing Causes of Death.

Background: To estimate risk of recurrence for women diagnosed with nonmetastatic breast cancer considering the risks of other causes mortality.

Methods: We extend a method based on the diagnosis-metastasis-death pathway to include risks of other causes mortality. We estimate three probabilities as cumulative incidence of: (i) being alive and recurrence-free, (ii) death for other causes before a recurrence, and (iii) recurrence.

A New Personalized Oral Cancer Survival Calculator to Estimate Risk of Death From Both Oral Cancer and Other Causes.

Importance: Standard cancer prognosis models typically do not include much specificity in characterizing competing illnesses or general health status when providing prognosis estimates, limiting their utility for individuals, who must consider their cancer in the context of their overall health. This is especially true for patients with oral cancer, who frequently have competing illnesses.

Objective: To describe a statistical framework and accompanying new publicly available calculator that provides personalized estimates of the probability of a patient surviving or dying from cancer or other causes, using oral cancer as the first data set.

Key Points for Clinicians About the SEER Oral Cancer Survival Calculator.

Importance: In the setting of a new cancer diagnosis, the focus is usually on the cancer as the main threat to survival, but people may have other conditions that pose an equal or greater threat to their life than their cancer: a competing risk of death. This is especially true for patients who have cancer of the oral cavity, because prolonged exposure to alcohol and tobacco are risk factors for cancer in this location but also can result in medical conditions with the potential to shorten life expectancy, competing as a cause of death that may intervene in conjunction with or before the cancer.

Observations: A calculator designed for public use has been released that allows patients age 20 to 86 years who have a newly diagnosed oral cancer to obtain estimates of their health status-adjusted age, life expectancy in the absence of the cancer, and probability of surviving, dying of the cancer, or dying of other causes within 1 to 10 years after diagnosis.

Protective effect of low-level laser irradiation on lipopolysaccharide-mediated inflammatory injury of human periodontal ligament fibroblasts.

Objectives: To study the effect and mechanism of low-level laser irradiation (LLLI) on lipopolysaccharide (LPS)-induced inflammatory injury of human periodontal ligament fibroblasts (hPDLFs).

Methods: hPDLFs were inoculated into well plates and randomly divided into the normal group, LPS group, and LPS+LLLI group. The cells in the normal group were cultured in conventional medium.

Effect of using diode laser on Enterococcus faecalis and its lipoteichoic acid (LTA) in chronic apical periodontitis.

The purpose of this study was to evaluate the effect of diode laser irradiation on Enterococcus faecalis (E. faecalis) and its lipoteichoic acid (LTA). Ninety-six freshly extracted single-rooted teeth were divided into six groups, n = 8 per group.

Exposure to diode laser (810nm) affects the bacterial adherence and biofilm formation in a E. faecalis biofilm model.

Background: A large number of studies have shown that diode laser can effectively kill Enterococcus faecalis (E. faecalis). However, to our knowledge there has been little information regarding high-level analysis of sterilization mechanism on E.

Analyzing discrete competing risks data with partially overlapping or independent data sources and nonstandard sampling schemes, with application to cancer registries.

This paper demonstrates the flexibility of a general approach for the analysis of discrete time competing risks data that can accommodate complex data structures, different time scales for different causes, and nonstandard sampling schemes. The data may involve a single data source where all individuals contribute to analyses of both cause-specific hazard functions, overlapping datasets where some individuals contribute to the analysis of the cause-specific hazard function of only one cause while other individuals contribute to analyses of both cause-specific hazard functions, or separate data sources where each individual contributes to the analysis of the cause-specific hazard function of only a single cause. The approach is modularized into estimation and prediction.

Can We Use Survival Data from Cancer Registries to Learn about Disease Recurrence? The Case of Breast Cancer.

Population-representative risks of metastatic recurrence are not generally available because cancer registries do not collect data on recurrence. This article presents a novel method that estimates the risk of recurrence using cancer registry disease-specific survival. The method is based on an illness-death process coupled with a mixture cure model for net cancer survival.

Statistical inferences of extended concentration indices for directly standardized rates.

The relative concentration index (RCI) and the absolute concentration index (ACI) have been widely used for monitoring health disparities with ranked health determinants. The RCI has been extended to allow value judgments about inequality aversion by Pereira in 1998 and by Wagstaff in 2002. Previous studies of the extended RCI have focused on survey sample data.

Geographical, racial and socio-economic variation in life expectancy in the US and their impact on cancer relative survival.

Purpose: Despite gains in life expectancy between 1992 to 2012, large disparities in life expectancy continue to exist in the United States between subgroups of the population. This study aimed to develop detailed life tables (LT), accounting for mortality differences by race, geography, and socio-economic status (SES), to more accurately measure relative cancer survival and life expectancy patterns in the United States.

Methods: We estimated an extensive set of County SES-LT by fitting Poisson regression models to deaths and population counts for U.

Early estimates of cancer incidence for 2015: Expanding to include estimates for white and black races.

Background: The National Cancer Institute's cancer incidence estimates through 2015 from the Surveillance, Epidemiology, and End Results (SEER) registries' November 2017 submission are released in April 2018.

Methods: Early estimates (February 2017) of cancer incidence rates and trends from the SEER 18 registries for diagnoses in 2000 through 2015 were evaluated with a revised delay-adjustment model, which was used to adjust for the undercount of cases in the early release. For the first time, early estimates were produced for race (whites and blacks) along with estimates for new sites: the oral cavity and pharynx, leukemia, and myeloma.

Prioritizing US Cervical Cancer Prevention With Results From a Geospatial Model.

Purpose: To determine if differences in screening and vaccination patterns across the population may accentuate ethnic and geographic variation in future burden of disease.

Methods: Using Cancer in North America data provided by the North American Association of Central Cancer Registries, county cervical cancer incidence trends from 1995 to 2009 were modeled for the entire United States using ecologic covariates. Rates for health service areas were also modeled by ethnicity.

Early estimates of SEER cancer incidence, 2014.

Background: Cancer incidence rates and trends for cases diagnosed through 2014 using data reported to the Surveillance, Epidemiology, and End Results (SEER) program in February 2016 and a validation of rates and trends for cases diagnosed through 2013 and submitted in February 2015 using the November 2015 submission are reported. New cancer sites include the pancreas, kidney and renal pelvis, corpus and uterus, and childhood cancer sites for ages birth to 19 years inclusive.

Methods: A new reporting delay model is presented for these estimates for more consistent results with the model used for the usual November SEER submissions, adjusting for the large case undercount in the February submission.

Geographic variation of intrahepatic cholangiocarcinoma, extrahepatic cholangiocarcinoma, and hepatocellular carcinoma in the United States.

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.

The Surveillance, Epidemiology, and End Results Cancer Survival Calculator SEER*CSC: validation in a managed care setting.

Background: Nomograms for prostate and colorectal cancer are included in the Surveillance, Epidemiology, and End Results (SEER) Cancer Survival Calculator, under development by the National Cancer Institute. They are based on the National Cancer Institute's SEER data, coupled with Medicare data, to estimate the probabilities of surviving or dying from cancer or from other causes based on a set of patient and tumor characteristics. The nomograms provide estimates of survival that are specific to the characteristics of the tumor, age, race, gender, and the overall health of a patient.

Cancer statistics, 2014.

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.

Adjusting for reporting delay in cancer incidence when combining different sets of cancer registries.

Cancer registries collect cancer incidence data that can be used to calculate incidence rates in a population and track changes over time. For incidence rates to be accurate, it is critical that diagnosed cases be reported in a timely manner. Registries typically allow a fixed amount of time (e.

The Cancer Survival Query System: making survival estimates from the Surveillance, Epidemiology, and End Results program more timely and relevant for recently diagnosed patients.

Background: Population-based cancer registries that include patient follow-up generally provide information regarding net survival (ie, survival associated with the risk of dying of cancer in the absence of competing risks). However, registry data also can be used to calculate survival from cancer in the presence of competing risks, which is more clinically relevant.

Methods: Statistical methods were developed to predict the risk of death from cancer and other causes, as well as natural life expectancy if the patient did not have cancer based on a profile of prognostic factors including characteristics of the cancer, demographic factors, and comorbid conditions.

A Weighted-Least-Squares Estimation Approach to Comparing Trends in Age-Adjusted Cancer Rates Across Overlapping Regions.

Li and Tiwari (2008) recently developed a corrected Z-test statistic for comparing the trends in cancer age-adjusted mortality and incidence rates across overlapping geographic regions, by properly adjusting for the correlation between the slopes of the fitted simple linear regression equations. One of their key assumptions is that the error variances have unknown but common variance. However, since the age-adjusted rates are linear combinations of mortality or incidence counts, arising naturally from an underlying Poisson process, this constant variance assumption may be violated.

Predicting US- and state-level cancer counts for the current calendar year: Part II: evaluation of spatiotemporal projection methods for incidence.

Background: The current study was undertaken to evaluate the spatiotemporal projection models applied by the American Cancer Society to predict the number of new cancer cases.

Methods: Adaptations of a model that has been used since 2007 were evaluated. Modeling is conducted in 3 steps.

U.S. geographic distribution of prevaccine era cervical cancer screening, incidence, stage, and mortality.

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.

Covariate adjusted weighted normal spatial scan statistics with applications to study geographic clustering of obesity and lung cancer mortality in the United States.

In the field of cluster detection, a weighted normal model-based scan statistic was recently developed to analyze regional continuous data and to evaluate the clustering pattern of pre-defined cells (such as state, county, tract, school, hospital) that include many individuals. The continuous measures of interest are, for example, the survival rate, mortality rate, length of physical activity, or the obesity measure, namely, body mass index, at the cell level with an uncertainty measure for each cell. In this paper, we extend the method to search for clusters of the cells after adjusting for single/multiple categorical/continuous covariates.

Interval Estimation for Ratios of Correlated Age-Adjusted Rates.

Providing reliable estimates of the ratios of cancer incidence and mortality rates across geographic regions has been important for the National cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) Program as it profiles cancer risk factors as well decides cancer control planning. A fundamental difficulty, however, arises when such ratios have to be computed to compare the rate of a subregion (e.g.

An age-stratified poisson model for comparing trends in cancer rates across overlapping regions.

The annual percent change (APC) has been used as a measure to describe the trend in the age-adjusted cancer incidence or mortality rate over relatively short time intervals. The yearly data on these age-adjusted rates are available from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. The traditional methods to estimate the APC is to fit a linear regression of logarithm of age-adjusted rates on time using the least squares method or the weighted least squares method, and use the estimate of the slope parameter to define the APC as the percent change in the rates between two consecutive years.

Efficient interval estimation for age-adjusted cancer rates.

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.