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. The models in the calculator showed that patients with oral cavity cancer had a higher than average risk of death from other causes than the matched US population, and this risk increases by stage. Conclusions and Relevance: The Surveillance, Epidemiology and End Results Program Oral Cancer Survival Calculator supports a holistic approach to the life of the patient, and the risk of death of other causes is treated equally to consideration of the probability of death of the cancer. This tool may be usefully paired with the other available prognostic calculators for oral cancer and is an example of the possibilities now available with registry linkages to partially overlapping or independent data sets and statistical techniques that allow the use of 2 time scales in 1 analysis.

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. Design, Setting, and Participants: The models used data from the Surveillance, Epidemiology, and End Results (SEER) 18 registry (2000 to 2011), SEER-Medicare linked files, and the National Health Interview Survey (NHIS) (1986 to 2009). Statistical methods developed to calculate natural life expectancy in the absence of the cancer, cancer-specific survival, and other-cause survival were applied to oral cancer data and internally validated with 10-fold cross-validation. Eligible participants were aged between 20 and 94 years with oral squamous cell carcinoma. Exposures: Histologically confirmed oral cancer, general health status, smoking, and selected serious comorbid conditions. Main Outcomes and Measures: Probabilities of surviving or dying from the cancer or from other causes, and life expectancy in the absence of the cancer. Results: A total of 22 392 patients with oral squamous cell carcinoma (13 544 male [60.5%]; 1476 Asian and Pacific Islander [6.7%]; 1792 Black [8.0%], 1589 Hispanic [7.2%], 17 300 White [78.1%]) and 402 626 NHIS interviewees were included in this calculator designed for public use for patients ages 20 to 86 years with newly diagnosed oral cancer to obtain estimates of health status-adjusted age, life expectancy in the absence of the cancer, and the probability of surviving, dying from the cancer, or dying from other causes within 1 to 10 years after diagnosis. The models in the calculator estimated that patients with oral cancer have a higher risk of death from other causes than their matched US population, and that this risk increases by stage. Conclusions and relevance: The models developed for the calculator demonstrate that survival estimates that exclude the effects of coexisting conditions can lead to underestimates or overestimates of survival. This new calculator approach will be broadly applicable for developing future prognostic models of cancer and noncancer aspects of a person's health in other cancers; as registries develop more linkages, available covariates will become broader, strengthening future tools.

Estimating life expectancy adjusted by self-rated health status in the United States: national health interview survey linked to the mortality.

BACKGROUND: Life expectancy is increasingly incorporated in evidence-based screening and treatment guidelines to facilitate patient-centered clinical decision-making. However, life expectancy estimates from standard life tables do not account for health status, an important prognostic factor for premature death. This study aims to address this research gap and develop life tables incorporating the health status of adults in the United States. METHODS: Data from the National Health Interview Survey (1986-2004) linked to mortality follow-up through to 2006 (age ≥ 40, n = 729,531) were used to develop life tables. The impact of self-rated health (excellent, very good, good, fair, poor) on survival was quantified in 5-year age groups, incorporating complex survey design and weights. Life expectancies were estimated by extrapolating the modeled survival probabilities. RESULTS: Life expectancies incorporating health status differed substantially from standard US life tables and by health status. Poor self-rated health more significantly affected the survival of younger compared to older individuals, resulting in substantial decreases in life expectancy. At age 40 years, hazards of dying for white men who reported poor vs. excellent health was 8.5 (95% CI: 7.0,10.3) times greater, resulting in a 23-year difference in life expectancy (poor vs. excellent: 22 vs. 45), while at age 80 years, the hazards ratio was 2.4 (95% CI: 2.1, 2.8) and life expectancy difference was 5 years (5 vs. 10). Relative to the US general population, life expectancies of adults (age < 65) with poor health were approximately 5-15 years shorter. CONCLUSIONS: Considerable shortage in life expectancy due to poor self-rated health existed. The life table developed can be helpful by including a patient perspective on their health and be used in conjunction with other predictive models in clinical decision making, particularly for younger adults in poor health, for whom life tables including comorbid conditions are limited.

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. For the estimation step, the parameters and the variance-covariance matrix can be estimated using widely available software. The prediction step utilizes a generic program with plug-in estimates from the estimation step. The approach is illustrated with three prognostic models for stage IV male oral cancer using different data structures. The first model uses only men with stage IV oral cancer from population-based registry data. The second model strategically extends the cohort to improve the efficiency of the estimates. The third model improves the accuracy for those with a lower risk of other causes of death, by bringing in an independent data source collected under a complex sampling design with additional other-cause covariates. These analyses represent novel extensions of existing methodology, broadly applicable for the development of prognostic models capturing both the cancer and noncancer aspects of a patient's health.

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. These nomograms have been internally validated using the SEER data. In this paper, we externally validate the nomograms using data from Kaiser Permanente Colorado. METHODS: The SEER Cancer Survival Calculator was externally validated using time-dependent area under the Receiver Operating Characteristic curve statistics and calibration plots for retrospective cohorts of 1102 prostate cancer and 990 colorectal cancer patients from Kaiser Permanente Colorado. RESULTS: The time-dependent area under the Receiver Operating Characteristic curve statistics were computed for one, three, five, seven, and 10 year(s) postdiagnosis for prostate and colorectal cancer and ranged from 0.77 to 0.89 for death from cancer and from 0.72 to 0.81 for death from other causes. The calibration plots indicated a very good fit of the model for death from cancer for colorectal cancer and for the higher risk group for prostate cancer. For the lower risk groups for prostate cancer (<10% chance of dying of prostate cancer in 10 years), the model predicted slightly worse prognosis than observed. Except for the lowest risk group for colorectal cancer, the models for death from other causes for both prostate and colorectal cancer predicted slightly worse prognosis than observed. CONCLUSIONS: The results of the external validation indicated that the colorectal and prostate cancer nomograms are reliable tools for physicians and patients to use to obtain information on prognosis and assist in establishing priorities for both treatment of the cancer and other conditions, particularly when a patient is elderly and/or has significant comorbidities. The slightly better than predicted risk of death from other causes in a health maintenance organization (HMO) setting may be due to an overall healthier population and the integrated management of disease relative to the overall population (as represented by SEER).

Comorbidity-adjusted life expectancy: a new tool to inform recommendations for optimal screening strategies.

BACKGROUND: Many guidelines recommend considering health status and life expectancy when making cancer screening decisions for elderly persons. OBJECTIVE: To estimate life expectancy for elderly persons without a history of cancer, taking into account comorbid conditions. DESIGN: Population-based cohort study. SETTING: A 5% sample of Medicare beneficiaries in selected geographic areas, including their claims and vital status information. PARTICIPANTS: Medicare beneficiaries aged 66 years or older between 1992 and 2005 without a history of cancer (n = 407 749). MEASUREMENTS: Medicare claims were used to identify comorbid conditions included in the Charlson index. Survival probabilities were estimated by comorbidity group (no, low/medium, and high) and for the 3 most prevalent conditions (diabetes, chronic obstructive pulmonary disease, and congestive heart failure) by using the Cox proportional hazards model. Comorbidity-adjusted life expectancy was calculated based on comparisons of survival models with U.S. life tables. Survival probabilities from the U.S. life tables providing the most similar survival experience to the cohort of interest were used. RESULTS: Persons with higher levels of comorbidity had shorter life expectancies, whereas those with no comorbid conditions, including very elderly persons, had favorable life expectancies relative to an average person of the same chronological age. The estimated life expectancy at age 75 years was approximately 3 years longer for persons with no comorbid conditions and approximately 3 years shorter for those with high comorbidity relative to the average U.S. population. LIMITATIONS: The cohort was limited to Medicare fee-for-service beneficiaries aged 66 years or older living in selected geographic areas. Data from the Surveillance, Epidemiology, and End Results cancer registry and Medicare claims lack information on functional status and severity of comorbidity, which might influence life expectancy in elderly persons. CONCLUSION: Life expectancy varies considerably by comorbidity status in elderly persons. Comorbidity-adjusted life expectancy may help physicians tailor recommendations for stopping or continuing cancer screening for individual patients.

Life tables adjusted for comorbidity more accurately estimate noncancer survival for recently diagnosed cancer patients.

OBJECTIVES: To provide cancer patients and clinicians with more accurate estimates of a patient's life expectancy with respect to noncancer mortality, we estimated comorbidity-adjusted life tables and health-adjusted age. STUDY DESIGN AND SETTING: Using data from the Surveillance Epidemiology and End Results-Medicare database, we estimated comorbidity scores that reflect the health status of people who are 66 years of age and older in the year before cancer diagnosis. Noncancer survival by comorbidity score was estimated for each age, race, and sex. Health-adjusted age was estimated by systematically comparing the noncancer survival models with US life tables. RESULTS: Comorbidity, cancer status, sex, and race are all important predictors of noncancer survival; however, their relative impact on noncancer survival decreases as age increases. Survival models by comorbidity better predicted noncancer survival than the US life tables. The health-adjusted age and national life tables can be consulted to provide an approximate estimate of a person's life expectancy, for example, the health-adjusted age of a black man aged 75 years with no comorbidities is 67 years, giving him a life expectancy of 13 years. CONCLUSION: The health-adjusted age and the life tables adjusted by age, race, sex, and comorbidity can provide important information to facilitate decision making about treatment for cancer and other conditions.

Serum macrophage inhibitory cytokine-1 (MIC-1/GDF15): a potential screening tool for the prevention of colon cancer?

BACKGROUND: Macrophage inhibitory cytokine-1 (MIC-1/GDF15) mediates nonsteroidal anti-inflammatory drug (NSAID) protection from colonic polyps in mice and is linked to the development of colorectal carcinoma in humans. Therefore, changes in serum MIC-1/GDF15 levels could predict the presence of premalignant colonic polyposis and assist in population screening strategies. METHODS: Serum MIC-1/GDF15 levels were measured in subjects in the Polyp Prevention Trial, in which NSAID use and colon cancer risk factors were defined. Subjects had an initial adenoma removed, a repeat colonoscopy removing previously unidentified polyps, and serum MIC-1/GDF15 estimation. Three years later recurrent adenomas were identified and serum MIC-1/GDF15 levels reestimated. The relationship between serum MIC-1/GDF15 levels and adenoma presence or recurrence was examined. RESULTS: Serum MIC-1/GDF15 levels differed by adenoma status and were significantly related to colon cancer risk factors. In addition, mean serum MIC-1/GDF15 levels rose with increasing numbers of adenomas present and high-risk adenoma recurrence. NSAID users had higher serum MIC-1/GDF15 concentrations, which were related to protection from adenoma recurrence. Furthermore, adjusted serum MIC-1/GDF15 levels at final follow-up were related to adenoma recurrence (highest quartile MIC-1/GDF15; OR = 14.7, 95% CI: 3.0-73). CONCLUSIONS: These data suggest that MIC-1/GDF15 mediates at least some of the protection afforded by NSAIDs against human colonic polyposis. Furthermore, serum MIC-1/GDF15 levels vary with the development of adnenomatous colonic polyps. IMPACT: Serum MIC-1/GDF15 determination may hold promise as the first serum screening test to assist the detection of premalignant adenomatous colonic polyposis.

Development of a prognostic model for six-month mortality in older adults with declining health.

CONTEXT: Estimation of six-month prognosis is essential in hospice referral decisions, but accurate, evidence-based tools to assist in this task are lacking. OBJECTIVES: To develop a new prognostic model, the Patient-Reported Outcome Mortality Prediction Tool (PROMPT), for six-month mortality in community-dwelling elderly patients. METHODS: We used data from the Medicare Health Outcomes Survey linked to vital status information. Respondents were 65 years old or older, with self-reported declining health over the past year (n=21,870), identified from four Medicare Health Outcomes Survey cohorts (1998-2000, 1999-2001, 2000-2002, and 2001-2003). A logistic regression model was derived to predict six-month mortality, using sociodemographic characteristics, comorbidities, and health-related quality of life (HRQOL), ascertained by measures of activities of daily living and the Medical Outcomes Study Short Form-36 Health Survey; k-fold cross-validation was used to evaluate model performance, which was compared with existing prognostic tools. RESULTS: The PROMPT incorporated 11 variables, including four HRQOL domains: general health perceptions, activities of daily living, social functioning, and energy/fatigue. The model demonstrated good discrimination (c-statistic=0.75) and calibration. Overall diagnostic accuracy was superior to existing tools. At cut points of 10%-70%, estimated six-month mortality risk sensitivity and specificity ranged from 0.8% to 83.4% and 51.1% to 99.9%, respectively, and positive likelihood ratios at all mortality risk cut points ≥40% exceeded 5.0. Corresponding positive and negative predictive values were 23.1%-64.1% and 85.3%-94.5%. Over 50% of patients with estimated six-month mortality risk ≥30% died within 12 months. CONCLUSION: The PROMPT, a new prognostic model incorporating HRQOL, demonstrates promising performance and potential value for hospice referral decisions. More work is needed to evaluate the model.

Prior history of non-melanoma skin cancer is associated with increased mortality in patients with chronic lymphocytic leukemia.

We investigated whether a previous diagnosis of non-melanoma skin cancer among chronic lymphocytic leukemia patients is a predictor of poor outcome. Using the Swedish Cancer Registry, we conducted a population-based study to evaluate the survival patterns among chronic lymphocytic leukemia patients with and without non-melanoma skin cancer. Cox proportional hazards regression models were used and Kaplan-Meier curves were constructed. Of a total of 12,041 chronic lymphocytic leukemia cases identified, 236 cases, including 111 squamous cell cancer, had a prior history of non-melanoma skin cancer. Chronic lymphocytic leukemia patients with a prior history of non-melanoma skin cancer had a 1.29-fold (95% CI 1.10-1.52; p=0.0024) increased risk of dying; and those with a history of squamous cell cancer had a further elevated 1.86-fold (95% CI 1.46-2.36; p<0.0001) risk of dying. Kaplan-Meier plots showed that patients with a history of non-melanoma skin cancer, particularly those with squamous cell cancer, had significantly poorer survival than chronic lymphocytic leukemia patients without non-melanoma skin cancer (p<0.0001; log-rank test). Non-melanoma skin cancer may be a novel clinical predictor of worse chronic lymphocytic leukemia outcome.

Hyperplastic polyps and the risk of adenoma recurrence in the polyp prevention trial.

BACKGROUND AND AIMS: Recent studies have suggested that some hyperplastic polyps may be associated with an increased risk of colorectal cancer. Prospective information on the risk of adenoma recurrence associated with hyperplastic polyps is limited. We sought to investigate whether the coexistence of hyperplastic polyps with adenomas increases the risk of adenoma recurrence. METHODS: We used unconditional logistic regression models to examine the association between baseline hyperplastic polyps and subsequent adenoma recurrence during a 3-year follow-up evaluation, among 1637 participants in the Polyp Prevention Trial. RESULTS: A total of 437 participants (26.7%) had hyperplastic polyps coexisting with adenomas at baseline. Of these, 132 (30.2%) had at least one hyperplastic polyp in the proximal colon, whereas 305 (69.8%) had only distal hyperplastic polyps. When compared with subjects without any hyperplastic polyps at baseline, there was no statistically significant association between the presence of baseline hyperplastic polyps and recurrence of any adenoma (odds ratio [OR], 1.19; 95% confidence interval [CI], 0.94-1.51) or advanced adenoma (OR, 1.25; 95% CI, 0.78-2.03). Also, there was no association between hyperplastic polyp location and adenoma recurrence (OR, 1.01; 95% CI, 0.69-1.48) for any proximal hyperplastic polyp (OR, 1.26; 95% CI, 0.96-1.65) and for distal hyperplastic polyps. CONCLUSIONS: The coexistence of hyperplastic polyps with adenomas, irrespective of location, does not confer an increased risk of adenoma recurrence beyond that of adenomas alone within 3 years of follow-up evaluation. Prospective long-term studies on adenoma recurrence risk associated with hyperplastic polyps in screening populations are needed.

Dopamine D2 receptor polymorphisms and adenoma recurrence in the Polyp Prevention Trial.

Epidemiological evidence suggests that obesity may be causally associated with colorectal cancer. Dopamine and the dopaminergic reward pathway have been implicated in drug and alcohol addiction as well as obesity. Polymorphisms within the D2 dopamine receptor gene (DRD2) have been shown to be associated with colorectal cancer risk. We investigated the association between DRD2 genotype at these loci and the risk of colorectal adenoma recurrence in the Polyp Prevention Trial. Odds ratios (OR) and 95% confidence intervals (CI) for risk of adenoma recurrence were calculated using unconditional logistic regression. Individuals with any, multiple (>or=2) or advanced adenoma recurrence after 4 years were compared to those without adenoma recurrence. Variation in intake of certain dietary components according to DRD2 genotype at 3 loci (rs1799732; rs6277; rs1800497) was also investigated. The DRD2 rs1799732 CT genotype was significantly associated with all adenoma recurrence (OR: 1.30; 95% CI: 1.01, 1.69). The rs1800497 TT genotype was also associated with a significantly increased risk of advanced adenoma recurrence (OR: 2.40; 95% CI: 1.11, 5.20). The rs1799732 CT and rs1800497 TT genotypes were significantly associated with adenoma recurrence in the Polyp Prevention Trial. Increased risk of adenoma recurrence as conferred by DRD2 genotypes may be related to difference in alcohol and fat intake across genotypes.

Polynucleotide kinase 3' phosphatase variant, dietary variables and risk of adenoma recurrence in the Polyp Prevention Trial.

Polymorphisms in a number of genes encoding for DNA repair enzymes have been associated with altering the function of these enzymes and increasing risk of a number of cancers, including colon cancer. We have investigated the association between a common variant in polynucleotide kinase 3' phosphatase (PNKP), a putative DNA repair enzyme, and risk of adenoma recurrence in the Polyp Prevention Trial participants. We also investigated possible interaction or effect modification between carriage of the variant allele, dietary components and risk of adenoma recurrence. Unconditional logistic regression models were used to calculate the odds ratios and 95% confidence intervals for an association between the G/T polymorphism, PNKP T5644G and risk of adenoma recurrence. We observed no association between carriage of the variant allele and risk of adenoma recurrence. Furthermore, we found no effect modification between genotype, dietary components and risk of adenoma recurrence. The PNKP T5644G variant does not seem to be involved in adenoma recurrence in the Polyp Prevention Trial.

Postpolypectomy colonoscopy surveillance guidelines: predictive accuracy for advanced adenoma at 4 years.

BACKGROUND: Lack of confidence in postpolypectomy surveillance guidelines may be a factor in the observed low adherence rates among providers. OBJECTIVE: To assess the 2006 postpolypectomy colonoscopy surveillance guidelines, which recommend 3-year follow-up colonoscopy for individuals with high-risk adenomas (defined as > or =3 adenomas or any advanced adenomas) and 5- to 10-year follow-up for patients with 2 or fewer nonadvanced adenomas, who are considered to be at low risk. DESIGN: Analysis of prospective data from the Polyp Prevention Trial. SETTING: United States. PARTICIPANTS: 1905 patients who had colorectal adenomas removed at baseline screening or diagnostic colonoscopy and completed the trial. MEASUREMENTS: Baseline adenoma characteristics, risk-stratified according to definitions used in the guidelines, were examined as predictors for advanced adenoma recurrence. RESULTS: 125 patients (6.6%) had advanced and 629 (33.0%) had nonadvanced adenoma recurrence; 1151 (60.4%) had no recurrence within 4 years of follow-up. The probability of advanced adenoma recurrence was 0.09 (95% CI, 0.07 to 0.11) among patients with high-risk adenomas at baseline and 0.05 (CI, 0.04 to 0.06) among those with low-risk adenomas at baseline. The relative risk for advanced adenoma recurrence for patients with high-risk adenomas versus those with low-risk adenomas at baseline was 1.68 (CI, 1.19 to 2.38) when advanced adenoma recurrence was compared with no advanced adenoma recurrence and 1.76 (CI, 1.26 to 2.46) when advanced adenoma recurrence was compared with no adenoma recurrence. The c-statistics for these 2 comparisons were 0.68 and 0.72, respectively. LIMITATION: Participants were self-selected and had restrictions on the degree of obesity. CONCLUSION: Although the risk for recurrence of advanced adenoma within 4 years is greater for patients with high-risk adenomas at baseline than for those with low-risk adenomas, the discrimination of this risk stratification scheme is relatively low.

Folate and MTHFR: risk of adenoma recurrence in the Polyp Prevention Trial.

BACKGROUND: Low dietary folate intake has been associated with colorectal cancer risk and adenoma recurrence. A C/T transition at position 677 in the gene encoding methlylenetetrahydrofolate reductase (MTHFR C677T) has been reported to interact with folate intake to modulate colorectal adenoma recurrence or cancer risk. METHODS: We investigated the association between MTHFR, total folate, and the risk of colorectal adenoma recurrence in the Polyp Prevention Trial. We compared 625 individuals with any adenoma recurrence after 4 years (266 individuals with multiple (> or =2) recurrent adenomas and 101 individuals with advanced adenoma recurrence) to 978 individuals with no adenoma recurrence. Odds ratios (OR) and 95% confidence intervals (CI) for risk of adenoma recurrence were calculated using unconditional logistic regression. We also investigated effect modification of the MTHFR genotype associations by total folate intake. RESULTS: In general, no statistically significant associations were found between quartile of folate intake (dietary or total) and adenoma recurrence. The MTHFR CT genotype was associated with a significantly increased risk of multiple adenoma recurrence (OR: 1.34, 95% CI: 1.00, 1.81). No significant interaction was noted for total folate and MTHFR genotype, though an increased risk of recurrence noted for the MTHFR CT genotype was statistically significant only for those individuals with below median intake of total folate. CONCLUSION: We report that the MTHFR 677 CT genotype was associated with increased risk of adenoma recurrence (specifically multiple adenoma recurrence) 4 years after polypectomy.

Estimating relative risks for common outcome using PROC NLP.

In cross-sectional or cohort studies with binary outcomes, it is biologically interpretable and of interest to estimate the relative risk or prevalence ratio, especially when the response rates are not rare. Several methods have been used to estimate the relative risk, among which the log-binomial models yield the maximum likelihood estimate (MLE) of the parameters. Because of restrictions on the parameter space, the log-binomial models often run into convergence problems. Some remedies, e.g., the Poisson and Cox regressions, have been proposed. However, these methods may give out-of-bound predicted response probabilities. In this paper, a new computation method using the SAS Nonlinear Programming (NLP) procedure is proposed to find the MLEs. The proposed NLP method was compared to the COPY method, a modified method to fit the log-binomial model. Issues in the implementation are discussed. For illustration, both methods were applied to data on the prevalence of microalbuminuria (micro-protein leakage into urine) for kidney disease patients from the Diabetes Control and Complications Trial. The sample SAS macro for calculating relative risk is provided in the appendix.

Steel factor controls midline cell death of primordial germ cells and is essential for their normal proliferation and migration.

During germ-cell migration in the mouse, the dynamics of embryo growth cause many germ cells to be left outside the range of chemoattractive signals from the gonad. At E10.5, movie analysis has shown that germ cells remaining in the midline no longer migrate directionally towards the genital ridges, but instead rapidly fragment and disappear. Extragonadal germ cell tumors of infancy, one of the most common neonatal tumors, are thought to arise from midline germ cells that failed to die. This paper addresses the mechanism of midline germ cell death in the mouse. We show that at E10.5, the rate of apoptosis is nearly four-times higher in midline germ cells than those more laterally. Gene expression profiling of purified germ cells suggests this is caused by activation of the intrinsic apoptotic pathway. We then show that germ cell apoptosis in the midline is activated by down-regulation of Steel factor (kit ligand) expression in the midline between E9.5 and E10.5. This is confirmed by the fact that removal of the intrinsic pro-apoptotic protein Bax rescues the germ-cell apoptosis seen in Steel null embryos. Two interesting things are revealed by this: first, germ-cell proliferation does not take place in these embryos after E9.0; second, migration of germ cells is highly abnormal. These data show first that changing expression of Steel factor is required for normal midline germ cell death, and second, that Steel factor is required for normal proliferation and migration of germ cells.