Individualized prediction of lung-function decline in chronic obstructive pulmonary disease.

BACKGROUND: The rate of lung-function decline in chronic obstructive pulmonary disease (COPD) varies substantially among individuals. We sought to develop and validate an individualized prediction model for forced expiratory volume at 1 second (FEV1) in current smokers with mild-to-moderate COPD. METHODS: Using data from a large long-term clinical trial (the Lung Health Study), we derived mixed-effects regression models to predict future FEV1 values over 11 years according to clinical traits. We modelled heterogeneity by allowing regression coefficients to vary across individuals. Two independent cohorts with COPD were used for validating the equations. RESULTS: We used data from 5594 patients (mean age 48.4 yr, 63% men, mean baseline FEV1 2.75 L) to create the individualized prediction equations. There was significant between-individual variability in the rate of FEV1 decline, with the interval for the annual rate of decline that contained 95% of individuals being -124 to -15 mL/yr for smokers and -83 to 15 mL/yr for sustained quitters. Clinical variables in the final model explained 88% of variation around follow-up FEV1. The C statistic for predicting severity grades was 0.90. Prediction equations performed robustly in the 2 external data sets. INTERPRETATION: A substantial part of individual variation in FEV1 decline can be explained by easily measured clinical variables. The model developed in this work can be used for prediction of future lung health in patients with mild-to-moderate COPD. TRIAL REGISTRATION: Lung Health Study - ClinicalTrials.gov, no. NCT00000568; Pan-Canadian Early Detection of Lung Cancer Study - ClinicalTrials.gov, no. NCT00751660.

Plasma pro-surfactant protein B and lung function decline in smokers.

Plasma pro-surfactant protein B (pro-SFTPB) levels have recently been shown to predict the development of lung cancer in current and ex-smokers, but the ability of pro-SFTPB to predict measures of chronic obstructive pulmonary disease (COPD) severity is unknown. We evaluated the performance characteristics of pro-SFTPB as a biomarker of lung function decline in a population of current and ex-smokers. Plasma pro-SFTPB levels were measured in 2503 current and ex-smokers enrolled in the Pan-Canadian Early Detection of Lung Cancer Study. Linear regression was performed to determine the relationship of pro-SFTPB levels to changes in forced expiratory volume in 1 s (FEV1) over a 2-year period as well as to baseline FEV1 and the burden of emphysema observed in computed tomography (CT) scans. Plasma pro-SFTPB levels were inversely related to both FEV1 % predicted (p=0.024) and FEV1/forced vital capacity (FVC) (p<0.001), and were positively related to the burden of emphysema on CT scans (p<0.001). Higher plasma pro-SFTPB levels were also associated with a more rapid decline in FEV1 at 1 year (p=0.024) and over 2 years of follow-up (p=0.004). Higher plasma pro-SFTPB levels are associated with increased severity of airflow limitation and accelerated decline in lung function. Pro-SFTPB is a promising biomarker for COPD severity and progression.

Hypertension is an independent predictor of survival disparity between African-American and white breast cancer patients.

The objective of this study was to determine whether comorbidity, or pre-existing conditions, can account for some of the disparity in survival between African-American and white breast cancer patients. A historical cohort study was conducted of 416 African-American and 838 white women diagnosed with breast cancer between 1973 and 1986, and followed through 1999 in the Kaiser Permanente Northern California Medical Care Program. Information on comorbidity, tumor characteristics and breast cancer treatment was obtained from medical records, and Surveillance, Epidemiology and End Results, Northern California Cancer Center Registry. Associations between comorbidity and survival were analyzed with multiple Cox proportional hazards regression. Over a mean follow-up of 9 years, African Americans had higher overall crude mortality than whites: 165 (39.7%) versus 279 (33.3%), respectively. When age, race, tumor characteristics and breast cancer treatment were controlled, the presence of hypertension was associated with all cause survival [hazard ratio (HR) = 1.33, 95% confidence intervals (CI) 1.07-1.67] and it accounted for 30% of racial disparity in this outcome. Hypertension-augmented Charlson Comorbidity Index was a significant predictor of survival from all causes (HR = 1.32, 95%CI 1.18-1.49), competing causes (HR = 1.52, 95%CI 1.32-1.76) and breast cancer specific causes (HR = 1.18, 95%CI 1.03-1.35). In conclusion, hypertension has prognostic significance in relation to survival disparity between African-American and white breast cancer patients. If our findings are replicated in contemporary cohorts, it may be necessary to include hypertension in the Charlson Comorbidity Index and other comorbidity measures.

Factors associated with human small aggressive non small cell lung cancer.

BACKGROUND: Some non-small cell lung cancers (NSCLC) progress to distant lymph nodes or metastasize while relatively small. Such small aggressive NSCLCs (SA-NSCLC) are no longer resectable with curative intent, carry a grave prognosis, and may involve unique biological pathways. This is a study of factors associated with SA-NSCLC. METHODS: A nested case-case study was embedded in the National Cancer Institute's Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. SA-NSCLC cases had stage T1, N3, and/or M1 NSCLC (n = 48) and non-SA-NSCLC cases had T2 to T3, N0 to N2, and M0 NSCLC (n = 329). Associations were assessed by multiple logistic regression. RESULTS: SA-NSCLCs were associated with younger age at diagnosis [odds ratio (OR)(>or=65 versus <65), 0.44; 95% confidence interval (95% CI), 0.22-0.88], female gender, family history of lung cancer, and the interaction gender*family history of lung cancer and were inversely associated with ibuprofen use (OR(yes versus no), 0.29; 95% CI, 0.11-0.76). The ORs for associating gender (women versus men) with SA-NSCLC in those with and without a family history of lung cancer were 11.76 (95% CI, 2.00-69.22) and 1.86 (95% CI, 0.88-3.96), respectively. These associations held adjusted for histology and time from screening to diagnosis and when alternative controls were assessed. CONCLUSION: SA-NSCLC was associated with female gender, especially in those with a family history of lung cancer. If these exploratory findings, which are subject to bias, are validated as causal, elucidation of the genetic and female factors involved may improve understanding of cancer progression and lead to preventions and therapies. Ibuprofen may inhibit lung cancer progression.

Comorbidity and survival disparities among black and white patients with breast cancer.

CONTEXT: Reasons for the shorter survival of black breast cancer patients compared with their white counterparts are not completely understood. OBJECTIVE: To evaluate the role of comorbidity in this racial disparity among breast cancer patients. DESIGN, SETTING, AND PATIENTS: Historical cohort from the Henry Ford Health System (a large comprehensive health system in Detroit, Mich) followed up for a median of 10 years. Patients (n = 906) included 264 black (29.1%) and 642 white (70.9%) women diagnosed as having breast cancer between 1985 and 1990. Detailed comorbidity data (268 comorbidities) and study data were abstracted from medical records and institutional, Surveillance, Epidemiology, and End Results, and Michigan State registries. Associations were analyzed with logistic and Cox regression. MAIN OUTCOME MEASURES: Breast cancer recurrence/progression and survival to death from all, breast cancer, and competing (non-breast cancer) causes. RESULTS: Of blacks, 64 (24.9%) died of breast cancer and 95 (37.0%) died of competing causes. Comparable data for whites were 115 (18.3%) and 202 (32.1%). Blacks had worse all-cause survival (hazard ratio [HR], 1.34; 95% confidence interval [CI], 1.11-1.62), breast cancer-specific survival (HR, 1.47; 95% CI, 1.08-2.00), and competing-causes survival (HR, 1.27; 95% CI, 1.00-1.63). A total of 77 adverse comorbidities were associated with reduced survival. Adverse comorbidity count was associated with all-cause (adjusted HR, 1.29; 95% CI, 1.19-1.40) and competing-causes survival but was not associated with recurrence/progression or breast cancer-specific survival. At least 1 adverse comorbidity was observed in 221 (86.0%) blacks and 407 (65.7%) whites (odds ratio, 3.20; 95% CI, 2.17-4.72). Comparisons of unadjusted and comorbidity-adjusted HRs indicated that adverse comorbidity explained 49.1% of all-cause and 76.7% of competing-causes survival disparity. Diabetes and hypertension were particularly important in explaining disparity. CONCLUSIONS: More black breast cancer patients die of competing causes than of breast cancer. Effective control of comorbidity in black breast cancer patients should help improve life expectancy and lead to a reduction in survival disparities.

In lung cancer patients, age, race-ethnicity, gender and smoking predict adverse comorbidity, which in turn predicts treatment and survival.

OBJECTIVE: This study evaluates the relationship between sociodemographic/exposure factors and comorbidity, and their impact on lung cancer treatment and survival. STUDY AND DESIGN SETTING: Data for 1,155 patients were abstracted from the Josephine Ford Cancer Center Tumor Registry and medical records. Associations were analyzed by linear, logistic, and Cox regression. RESULTS: Approximately 88% of patients had > or = 1 of 56 comorbidities assessed. In multivariate analysis, comorbidity count was associated with older age, pack-years smoked, heavy alcohol use, lower socioeconomic status (SES), and female gender. Approximately 63% of patients had > or = 1 of 18 adverse prognostic comorbidities (AC), and significant independent predictors of AC were age, pack-years, African-American race/ethnicity, and gender. In multivariate analysis, comorbidity count and AC predicted nonreceipt of surgery in localized disease (OR(> or = 1 vs. 0 AC)=0.38, 95% 0.18, 0.81) and chemotherapy in advanced disease (OR > or = 1 vs. 0 AC)=0.72, 95% 0.51, 1.00). In adjusted analysis, comorbidity predicted survival in localized (hazard ratio (HR)(> or = 2 vs. 0 AC)=2.99, 95% CI 1.75, 5.10) and advanced lung cancer (HR(> or = 2 vs. 0 AC)=1.56, 95% CI 1.25, 1.94). CONCLUSION: Comorbidity has important deleterious effects on lung cancer outcomes and significant predictors of comorbidity included age, smoking, race/ethnicity, SES, alcohol, and gender.

Smoking and lung cancer survival: the role of comorbidity and treatment.

STUDY OBJECTIVE: Numerous studies indicate that smoking is associated with poorer outcomes in patients with cancer. The aim of this study was to determine whether smoking independently predicts survival in patients with lung cancer or whether an existent effect is mediated through comorbidity and/or treatment. DESIGN AND SETTING: Cox proportional hazards analysis was used to study a cohort of 1,155 patients with lung cancer diagnosed at the Henry Ford Health System between 1995 and 1998, inclusive. RESULTS: Adjusted for the baseline covariates, age, gender, illicit drug use, adverse symptoms, histology, and stage, the hazard ratio (HR) for smoking (current vs former/never) was 1.37 (95% confidence interval [CI], 1.18 to 1.59; p < 0.001). Adjusted for the baseline covariates and for 18 deleterious comorbidities, the HR for smoking was 1.38 (95% CI, 1.18 to 1.60; p < 0.001), indicating that the hazardous effect of smoking was not mediated through comorbidity. Current smoking was inversely associated with treatment (any surgery and/or chemotherapy and/or radiation therapy vs none) [odds ratio, 0.73; 95% CI, 0.55 to 0.98 (p = 0.03)]. Adjusted for baseline covariates, comorbidities and treatment, the HR for current smoker vs former/never was 1.26 (95% CI, 1.08 to 1.47; p = 0.003), a decline of 30.7% explained by treatment (HR for any treatment vs none, 0.40; 95% CI, 0.33 to 0.48; p < 0.001). CONCLUSIONS: Current smoking at diagnosis is an important independent predictor of shortened lung cancer survival. That this effect was not explained by sociodemographic/exposure factors, adverse symptoms, histology, stage, comorbidity, and treatment suggests that it may be mediated through direct biological effects.

Comparing benefits from many possible computed tomography lung cancer screening programs: extrapolating from the National Lung Screening Trial using comparative modeling.

BACKGROUND: The National Lung Screening Trial (NLST) demonstrated that in current and former smokers aged 55 to 74 years, with at least 30 pack-years of cigarette smoking history and who had quit smoking no more than 15 years ago, 3 annual computed tomography (CT) screens reduced lung cancer-specific mortality by 20% relative to 3 annual chest X-ray screens. We compared the benefits achievable with 576 lung cancer screening programs that varied CT screen number and frequency, ages of screening, and eligibility based on smoking. METHODS AND FINDINGS: We used five independent microsimulation models with lung cancer natural history parameters previously calibrated to the NLST to simulate life histories of the US cohort born in 1950 under all 576 programs. 'Efficient' (within model) programs prevented the greatest number of lung cancer deaths, compared to no screening, for a given number of CT screens. Among 120 'consensus efficient' (identified as efficient across models) programs, the average starting age was 55 years, the stopping age was 80 or 85 years, the average minimum pack-years was 27, and the maximum years since quitting was 20. Among consensus efficient programs, 11% to 40% of the cohort was screened, and 153 to 846 lung cancer deaths were averted per 100,000 people. In all models, annual screening based on age and smoking eligibility in NLST was not efficient; continuing screening to age 80 or 85 years was more efficient. CONCLUSIONS: Consensus results from five models identified a set of efficient screening programs that include annual CT lung cancer screening using criteria like NLST eligibility but extended to older ages. Guidelines for screening should also consider harms of screening and individual patient characteristics.

Pro-surfactant protein B as a biomarker for lung cancer prediction.

PURPOSE: Preliminary studies have identified pro-surfactant protein B (pro-SFTPB) to be a promising blood biomarker for non-small-cell lung cancer. We conducted a study to determine the independent predictive potential of pro-SFTPB in identifying individuals who are subsequently diagnosed with lung cancer. PATIENTS AND METHODS: Pro-SFTPB levels were measured in 2,485 individuals, who enrolled onto the Pan-Canadian Early Detection of Lung Cancer Study by using plasma sample collected at the baseline visit. Multivariable logistic regression models were used to evaluate the predictive ability of pro-SFTPB in addition to known lung cancer risk factors. Calibration and discrimination were evaluated, the latter by an area under the receiver operating characteristic curve (AUC). External validation was performed with samples collected in the Carotene and Retinol Efficacy Trial (CARET) participants using a case-control study design. RESULTS: Adjusted for age, sex, body mass index, personal history of cancer, family history of lung cancer, forced expiratory volume in one second percent predicted, average number of cigarettes smoked per day, and smoking duration, pro-SFTPB (log transformed) had an odds ratio of 2.220 (95% CI, 1.727 to 2.853; P < .001). The AUCs of the full model with and without pro-SFTPB were 0.741 (95% CI, 0.696 to 0.783) and 0.669 (95% CI, 0.620 to 0.717; difference in AUC P < .001). In the CARET Study, the use of pro-SFPTB yielded an AUC of 0.683 (95% CI, 0.604 to 0.761). CONCLUSION: Pro-SFTPB in plasma is an independent predictor of lung cancer and may be a valuable addition to existing lung cancer risk prediction models.

Lung cancer risk prediction: Prostate, Lung, Colorectal And Ovarian Cancer Screening Trial models and validation.

INTRODUCTION: Identification of individuals at high risk for lung cancer should be of value to individuals, patients, clinicians, and researchers. Existing prediction models have only modest capabilities to classify persons at risk accurately. METHODS: Prospective data from 70 962 control subjects in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) were used in models for the general population (model 1) and for a subcohort of ever-smokers (N = 38 254) (model 2). Both models included age, socioeconomic status (education), body mass index, family history of lung cancer, chronic obstructive pulmonary disease, recent chest x-ray, smoking status (never, former, or current), pack-years smoked, and smoking duration. Model 2 also included smoking quit-time (time in years since ever-smokers permanently quit smoking). External validation was performed with 44 223 PLCO intervention arm participants who completed a supplemental questionnaire and were subsequently followed. Known available risk factors were included in logistic regression models. Bootstrap optimism-corrected estimates of predictive performance were calculated (internal validation). Nonlinear relationships for age, pack-years smoked, smoking duration, and quit-time were modeled using restricted cubic splines. All reported P values are two-sided. RESULTS: During follow-up (median 9.2 years) of the control arm subjects, 1040 lung cancers occurred. During follow-up of the external validation sample (median 3.0 years), 213 lung cancers occurred. For models 1 and 2, bootstrap optimism-corrected receiver operator characteristic area under the curves were 0.857 and 0.805, and calibration slopes (model-predicted probabilities vs observed probabilities) were 0.987 and 0.979, respectively. In the external validation sample, models 1 and 2 had area under the curves of 0.841 and 0.784, respectively. These models had high discrimination in women, men, whites, and nonwhites. CONCLUSION: The PLCO lung cancer risk models demonstrate high discrimination and calibration.

Secondhand smoke as a potential cause of chronic rhinosinusitis: a case-control study.

OBJECTIVE: To assess the role of secondhand smoke (SHS) in the etiology of chronic rhinosinusitis (CRS). DESIGN: Matched case-control study. Associations between SHS and CRS were evaluated by conditional logistic regression odds ratios. SETTING: Henry Ford Health System, Detroit, Michigan. PARTICIPANTS: A total of 306 nonsmoking patients diagnosed as having an incident case of CRS and 306 age-matched, sex-matched, and race/ethnicity-matched nonsmoking control patients. MAIN OUTCOME MEASURES: Exposure to SHS for the 5 years before diagnosis of CRS (case patients) and before study entry (controls) for 4 primary sources: home, work, public places, and private social functions outside the home, such as parties, dinners, and weddings. RESULTS: Of controls and case patients, respectively, 28 (9.1%) and 41 (13.4%) had SHS exposure at home, 21 (6.9%) and 57 (18.6%) at work, 258 (84.3%) and 276 (90.2%) in public places, and 85 (27.8%) and 157 (51.3%) at private social functions. Adjusted for potential confounders (socioeconomic status and exposures to air pollution and chemicals or respiratory irritants from hobbies, work, or elsewhere), the odds ratios for CRS were 1.69 (95% confidence interval, 0.92-3.10) for SHS exposure at home, 2.81 (1.42-5.57) for exposure at work, 1.48 (0.88-2.49) for exposure in public places, and 2.60 (1.74-3.89) for exposure at private functions. A strong, independent dose-response relationship existed between CRS and the number of venues where SHS exposure occurred (odds ratio per 1 of 4 levels, 2.03; 95% confidence interval, 1.55-2.66). Approximately 40.0% of CRS appeared to be attributable to SHS. CONCLUSIONS: Exposure to SHS is common and significantly independently associated with CRS. These findings have important clinical and public health implications.

Racial/ethnic disparities in breast and gynecologic cancer treatment and outcomes.

PURPOSE OF REVIEW: To review recent research in racial/ethnic disparities in breast and gynecologic cancers, focusing on disparities occurring postdiagnosis. RECENT FINDINGS: Mortality statistics show that of the cancers under study, breast cancer has the greatest impact, and of racial/ethnic groups, African Americans suffer the greatest disparities, with highest mortality rates for breast, uterine and cervical cancers, and second highest for ovarian cancer. Recent studies demonstrated that black breast cancer patients suffer more underuse of appropriate adjuvant therapy, and greater delays in diagnosis and institution of treatments, and blacks and Hispanics suffered greater postsurgical pain and symptomatology. Data indicate that the biology of some breast cancers in blacks is unique and more aggressive. One study demonstrated that more black breast cancer patients died of nonbreast cancer causes and that excessive comorbidity in blacks explained substantial amounts of survival disparity. Research is beginning to identify important disparities in nonblack minority racial/ethnic groups, including Hispanics and South Asian Americans. SUMMARY: Research is continuing to identify and explain an important group of disparities - African American disparities in breast cancer outcomes. Disparities in other minority racial/ethnic groups, and in ovarian, uterine and cervical cancers, are at an emerging stage. Continuing efforts at all fronts are needed.

Lung carcinoma symptoms--an independent predictor of survival and an important mediator of African-American disparity in survival.

BACKGROUND: The extent of disease in patients with lung carcinoma is reflected morphologically by stage and pathophysiologically by sign/symptoms. This study evaluates the associations between symptoms and stage, the independent impact of symptoms on survival, predictors of symptoms, and the extent to which symptoms mediate survival disparities. METHODS: Data from 1154 patients with lung carcinoma were collected from the authors' tumor registry and by abstraction of medical records. Associations were evaluated by logistic and Cox regression analyses. RESULTS: Symptomatic diagnoses were associated with advanced disease stage (odds ratio [OR], 4.53; 95% confidence interval [95%CI], 3.17-6.48). Hoarseness, hemoptysis, dyspnea, noncardiac chest pain, extrathoracic pain, neurologic symptoms, weight loss, and weakness/fatigue (adverse symptoms) were associated independently with relatively higher/advanced stage and/or reduced survival. Adverse symptoms (> or = 1 vs. 0) predicted reduced survival independently of stage and other prognosticators (hazard ratio [HR], 1.84; 95%CI, 1.52-2.21). Independent predictors of adverse symptoms included gender (OR(male vs. female), 1.50; 95%CI, 1.11-2.01), race/ethnicity (OR(black vs. white), 1.62; 95%CI, 1.18-2.21), and marital status (OR(spouseless vs. not), 1.79; 95%CI 1.31-2.45). The hazard ratios (HR; black vs white), univariate, adjusted for stage, and adjusted for stage and adverse symptoms, was 1.206 (95%CI, 1.05-1.38), 1.165 (95%CI, 1.01-1.34), and 1.075 (95%CI, 0.94-1.26), respectively. Adverse symptoms explained 43% of race/ethnic survival disparity beyond stage. CONCLUSIONS: Symptoms were associated with disease stage, yet both were important, independent predictors of survival; and symptoms explained an important amount of race/ethnic disparity in the survival of patients with lung carcinoma. Symptomatology needs to be incorporated into cancer clinical trials and into outcomes and disparities research.

Impact of comorbidity on lung cancer survival.

Lung cancer is associated with smoking and age, both of which are associated with comorbidity. We evaluated the impact of comorbidity on lung cancer survival. Data on 56 comorbidities were abstracted from the records of a cohort of 1,155 patients. Survival effects were evaluated with Cox regression (outcome crude death). The adjusted R(2) statistic was used to compare the survival variation explained by predictive variables. No comorbidity was observed in 11.7% of patients, while 54.3% had 3 or more (mean 2.97) comorbidities. In multivariate analysis, 19 comorbidities were associated with survival: HIV/AIDS, tuberculosis, previous metastatic cancer, thyroid/glandular diseases, electrolyte imbalance, anemia, other blood diseases, dementia, neurologic disease, congestive heart failure, COPD, asthma, pulmonary fibrosis, liver disease, gastrointestinal bleeding, renal disease, connective tissue disease, osteoporosis and peripheral vascular disease. Only the latter was protective. Some of the hazards of comorbidities were explained by more directly acting comorbidities and/or receipt of treatment. Stage explained 25.4% of the survival variation. In addition to stage, the 19 comorbidities explained 6.1%, treatments 9.2%, age 3.7% and histology 1.3%. Thirteen uncommon comorbidities (prevalence <6%) affected 21.2% of patients and explained 3.5% of the survival variation. Comorbidity count and the Charlson index were significant predictors but explained only 2.5% and 2.0% of the survival variation, respectively. Comorbidity has a major impact on survival in early- and late-stage disease, and even infrequent deleterious comorbidities are important collectively. Comorbidity count and the Charlson index failed to capture much information. Clinical practice and trials need to consider the effect of comorbidity in lung cancer patients.