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Supplemental Digital Content is Available in the Text. Neublastin showed some evidence of pain relief among patients with painful lumbosacral radiculopathy; however, there was no clear dose–response relationship., Neublastin (BG00010) is a first-in-class, glial cell–derived neurotrophic factor shown in preclinical studies and an early clinical trial to have potential for the treatment of neuropathic pain. SPRINT was a phase 2, multicenter, double-blinded, placebo-controlled study to evaluate efficacy/safety of 5 neublastin doses (50, 150, 400, 800, and 1200 μg/kg) administered as an intravenous injection 3 times/week for 1 week in patients with chronic painful lumbosacral radiculopathy, utilizing Bayesian response-adaptive study design. Primary endpoint was change from baseline in mean 24-hour average general pain intensity over a 5-day period (week 1) after the last dose, analyzed using a Bayesian normal dynamic linear model. One hundred seventy-six patients were randomized and received treatment (placebo n = 48, 50 μg/kg n = 38, 150 μg/kg n = 13, 400 μg/kg n = 16, 800 μg/kg n = 20, 1200 μg/kg n = 41). Among the tested neublastin doses, the lowest dose (50 μg/kg) showed the greatest difference from placebo for change from baseline in mean average general pain intensity at week 1 after last dose, followed by the highest dose (1200 μg/kg) (posterior mean difference −1.36 [95% credible interval −2.22 to −0.52] and −0.75 [−1.59 to 0.08], respectively). Similar trends were observed in secondary efficacy endpoints. The most common adverse event in all neublastin dose groups was pruritus (79% vs 10% with placebo). There was no dose–response relationship with respect to primary/secondary efficacy outcomes or incidence of pruritus, despite dose-proportional increases in serum neublastin concentrations. In conclusion, while this study showed some evidence of pain relief with neublastin, particularly at the lowest dose, there was no clear dose–response relationship for pain reduction or the most common adverse event of pruritus.

Alzheimer’s disease (AD) has increasingly been recognized as a huge unmet medical need. Currently, there is no approved drug to cure, prevent, or even slow down the disease. It is imperative to develop disease-modifying treatments for AD to alter the underlying disease progression. This paper reviews the most up-to-date regulatory guidance on how to demonstrate disease modification and provides an overview of available methodologies and applications to clinical trials. The intent is to assist the field with future clinical trials designed to demonstrate disease-modifying effect in AD. The methodologies may be generalizable to broader neurodegenerative diseases.

A large number of analgesics have failed to prove superiority over placebo in randomized controlled trials (RCTs), and as this has been related to increasing placebo responses, there is currently an interest in specifying predictors of the placebo response. The literature on placebo mechanisms suggests that factors related to patients' expectations of treatment efficacy are pivotal for the placebo response. Also, general characteristics of RCTs have been suggested to influence the placebo response. Yet, only few meta-analyses have directly tested these hypotheses. Placebo data from 9 industrially sponsored, randomized, double-blind, placebo-controlled, multicenter phase III trials in 2017 adult patients suffering from chronic painful osteoarthritis (hip or knee) or low back pain were included. The primary outcome was pain intensity. Based on previous studies, we chose 3 expectancy-related primary predictors: type of active medication, randomization ratio, and number of planned face-to-face visits. In addition, explorative analyses tested whether RCT and patients' characteristics predicted the placebo response. Opioid trials, a high number of planned face-to-face visits, and randomization ratio predicted the magnitude of the placebo response, thereby supporting the expectancy hypothesis. Exploratory models with baseline pain intensity, age, washout length, and discontinuation because of adverse events accounted for approximately 10% of the variability in the placebo response. Based on these results and previous mechanisms studies, we think that patients' perception of treatment allocation and expectations toward treatment efficacy could potently predict outcomes of RCTs.

(See the editorial commentary by Wittes on pages 1523–5.) Herpes zoster (HZ), caused by reactivation of latent varicella zoster virus (VZV) [1], entails rash and pain that decreases daily functioning and health-related quality of life, more so with increasing age [1–10]. The phase III Shingles Prevention Study (SPS) showed that the live, attenuated zoster vaccine (ZV; Zostavax, Merck, Whitehouse Station, NJ) had an estimated 51% vaccine efficacy (VE; 95% confidence interval [CI], 44%–58%) to reduce the incidence of HZ in persons aged ≥60 years [11]. Subsequently, another phase III Zostavax Efficacy and Safety Trial (ZEST) was conducted to assess the VE of ZV in persons aged 50–59 years and showed an estimated 70% VE (95% CI, 54%–81%) [12]. Secondary analyses of the SPS suggested that 3 different measures of VZV-specific immunity were correlated with protection from HZ: responder cell frequency–determined cell-mediated immunity (CMI), interferon γ (IFN-γ) enzyme-linked immunosorbent spot–determined CMI, and glycoprotein-based enzyme-linked immunosorbent assay (gpELISA)–determined antibody level [13]. Because the gpELISA is easier to use and more validated as a reproducible quantitative assay and because the combination of titers and fold rise appeared to best correlate with protection in the SPS [14], the ZEST included an objective to assess VZV antibody titers by gpELISA but not by the CMI measures as a correlate of protection (CoP). Both week 6 and fold rise in VZV antibody titers determined by gpELISA were strong inverse correlates of risk (CoRs) of HZ in vaccine recipients [15], where a CoR is defined as an immune biomarker that is associated with the rate of a study end point used to measure VE in a defined population [16]. Here we directly assess whether the identified CoRs are also good CoPs [16]. A CoP may be defined as an immune biomarker measuring a response to vaccination that reliably predicts the level of VE to prevent a clinically meaningful end point. The literature on approaches for assessing CoPs has used different meanings for the term “CoP,” with no consensus [16–20]. Plotkin and Gilbert [21] advocated for the common use of the definition specified above, which is solely about reliable statistical prediction and is silent about whether the biomarker is also a mechanism of protection. These authors also advocated for annotating CoPs as mCoPs (mechanistic CoPs) or nCoPs (nonmechanistic CoPs) for scenarios in which experiments have determined whether the biomarker is a true mechanism of protection. Validated CoPs benefit vaccine development by serving as reliable surrogate end points for true clinical end points of interest, thereby allowing using surrogate end points in phase I and II trials to provide reliable answers about clinical VE without requiring phase III field trials. Validated CoPs confer many other benefits, as extensively discussed elsewhere [16–20, 22]. Given that reliable prediction of VE is very useful in itself, even as a so-called black box predictor with no associated mechanism, nCoPs and mCoPs are highly beneficial for vaccine development. The concept of a CoP is the same as a valid surrogate end point in the clinical trials statistical literature. Two major statistical frameworks have been developed for assessing the validity of a surrogate end point based on an efficacy trial, the Prentice framework [16, 23–25] and the principal stratification or VE curve framework [26, 27]. While both are useful for assessing the validity of the candidate gpELISA CoPs, this article focuses on the VE curve framework. This approach directly estimates the VE curve, defined as the VE against the clinical end point for each of a spectrum of participant subgroups defined by their biomarker readout measuring vaccine-induced immune response. The major challenge posed to using this approach is that the vaccine-induced immune response is only measured in subjects assigned to receive the vaccine (it is unknown in subjects assigned to receive placebo). Consequently, its effective application requires availability of a subject characteristic before immunization that predicts the candidate CoP [28]; such a baseline immunogenicity predictor (BIP) allows inclusion of an estimate of the immune response to the vaccine that placebo recipients would have had had they been vaccinated, thereby enabling estimation of the VE curve. This approach can be used for estimating the VE curve for subgroups defined either by levels of the vaccine-induced immune response or by both the levels of this response and the response under assignment to placebo. Several statistical methods have been developed for estimating the VE curve based on a BIP [27–32]. However, because adequately predictive BIPs have not been available, the methods have not yet been effectively applied. Fortunately, a high-quality BIP is available in the ZEST, and here we report, for the first time, an application of this framework to produce clear results that validate one biomarker as an excellent CoP (fold rise in gpELISA titers) and another biomarker as a poor CoP (week 6 gpELISA titers). By directly assessing how VE varies with participant subgroups defined by gpELISA readouts, this framework provides clearly interpretable results that lend themselves to central applications, such as comparing the utility of different immune response biomarkers as CoPs and estimating seroprotection levels.

Our objective is to test disparities in breast cancer mortality by sexual orientation. Using an ecological approach that links SEER breast cancer mortality data with Census 2000 data, we test the hypothesis of higher breast cancer mortality in areas with more presumed lesbians. From the Census 2000 data on female same-sex partnered households, we derive a measure of sexual minority women density (SMWD) for each of the 215 counties covered by SEER 12. We test the association of SMWD with breast cancer mortality using multivariable Poisson regression models that control for age, race, and socioeconomic status. We confirm our hypothesis as we find a significant positive association between SMWD and breast cancer mortality. This relationship remains significant even after controlling for other factors, known to have an association with mortality, such as poverty or race. This ecological approach compensates for the absence of cancer surveillance by sexual orientation. The results suggest a disparity in breast cancer mortality due to sexual orientation. The causes for this disparity need to be identified by future studies.

This study identifies differences by sexual orientation in health behaviors of cancer survivors.We pooled data from the 2001, 2003, and 2005 California health interview survey to compare cancer survivors' alcohol use, smoking, exercise, fruit and vegetable consumption, weight, and physician visits by sexual orientation.Female bisexual cancer survivors were 2.2 times more likely to report being a current smoker and were 0.39 times less likely to report physical inactivity compared with female heterosexual cancer survivors. Lesbian cancer survivors were 7.4 times more likely to have visited a physician during the past year than female heterosexual cancer survivors. Among male cancer survivors, both gay and bisexual men had significantly lower odds (OR = 0.4) of being overweight or obese, and bisexual men were 3.0 times more likely to engage in vigorous activity and 7.8 times more likely to visit physicians compared with heterosexual men.This study's prevalence estimates of behavioral risk factors of gay, lesbian, and bisexual cancer survivors suggest considerable need for promotion of healthy lifestyle behaviors. We discuss the need for future studies with lesbian, gay, and bisexual cancer survivors.

Summary Objectives To determine whether there is an association between geographical areas with greater sexual minority density, defined as gay and lesbian individuals, and incidence and mortality rates for lung cancer. Study design As individual surveillance data on sexual orientation are not available, this study used an ecological approach to examine the link between sexual minorities and lung cancer. Methods Population-based surveillance data on the incidence of and mortality due to lung cancer from 1996 to 2004 were used from 12 Surveillance, Epidemiology and End Results (SEER) registries and 2000 Census data on same-sex-partnered households for the geographical area covered by SEER 12. Using multiple regression models, the county-level association of sexual minority density with incidence or mortality rates for lung cancer was examined. Results A significant positive association was found between both incidence and mortality rates for lung cancer and areas with a higher density of sexual minority men, and a significant negative association was found between both incidence and mortality rates for lung cancer and areas with a higher density of sexual minority women. Conclusions In the absence of surveillance data, this novel methodological strategy approximates population-level lung cancer disparities for sexual minority populations at the aggregate level.

We present a nonparametric test to validate surrogate endpoints based on measure of divergence and random permutation. This test is a proposal to directly verify the Prentice statistical definition of surrogacy. The test does not impose distributional assumptions on the endpoints, and it is robust to model misspecification. Our simulation study shows that the proposed nonparametric test outperforms the practical test of the Prentice criterion in terms of both robustness of size and power. We also evaluate the performance of three leading methods that attempt to quantify the effect of surrogate endpoints. The proposed method is applied to validate magnetic resonance imaging lesions as the surrogate endpoint for clinical relapses in a multiple sclerosis trial. Copyright © 2012 John Wiley & Sons, Ltd.

Objectives. We estimated differences in health behaviors among adults by sexual orientation. Methods. We pooled 4 years of data (2001, 2003, 2005, and 2007) from the California Health Interview Survey. We estimated the frequency of smoking, alcohol use, healthy dietary behaviors, physical activity, and health care utilization, and we used logistic regression modeling to determine the odds of each behavior with increasing age and for 2 age groups: younger than 50 years and 50 years old or older. Results. At any adult age, lesbians had greater odds of smoking and binge drinking than did heterosexual women, and gay and bisexual men had greater health care utilization than did heterosexual men. Other risk behaviors differed with age. Conclusions. Some behavioral change interventions should target lesbians, gays, and bisexuals at all ages, whereas other interventions should specifically target individuals at younger ages.

Sexual minorities engage in more risk behaviors at a younger age than heterosexuals and many are subject to minority stress from a young age, which raises questions about the age at which sexual minorities' experience morbidities. Our objective was to estimate the prevalence of health conditions among young, middle age, and older age groups to examine sexual orientation differences while stratifying by gender.We pooled 4 years of data from the California Health Interview Survey to obtain a representative sample of the male and female population in California, allowing us to examine health conditions by sexual orientation in three age strata, age 20-39, age 40-59, and age 60 and older.Compared with same-gender heterosexuals, sexual minority women had a higher likelihood of physical morbidities (disability: adjusted odds ratio [AOR] 2.66 for lesbians and AOR 2.21 for bisexuals; arthritis: AOR 2.12 for lesbians) at a young age, whereas gay men had a higher likelihood of heart disease (AOR 2.78) and cancer (AOR 4.75) at a young age. Across the life span, sexual minorities had higher likelihoods of poor mental health than heterosexuals.These findings suggest that at a young age, sexual minorities experience more morbidities than heterosexual individuals. Consideration should be given to early detection, identification, and treatment of these conditions among sexual minorities particularly at younger ages.

By combining hydrogen bonding layer-by-layer self-assembly and the stepwise chemisorption method, a new alternating polymer adsorption/surface activation self-assembly method was developed. First a layer of diphenylamine-4-diazonium-formaldehyde resin (diazo resin or DR) is deposited on a substrate. In the following surface activation step, the diazonium groups on the surface couple with resorcin in the outside solution. The deposition of another layer of DR is feasible due to the formation of hydrogen bond between the diazonium group of DR and the hydroxy group of the resorcin moieties. The resulting film is photosensitive. After UV irradiation, the film becomes very stable towards polar organic solvents.

The concept of principal surrogate developed in the causal inference framework (Frangakis and Rubin (Biometrics 58:21–29, 2002); Gilbert and Hudgens (Biometrics 64:1146–1154, 2008)) has drawn much attention in the field of biomarker research. Principal surrogates are defined based on the causal treatment effects in principal strata, which are constructed based on the joint distribution of the potential surrogate markers when a patient receives either the placebo or the treatment. The challenge of evaluating principal surrogates lies in the fact that half of these potential surrogate markers cannot be observed in most clinical trials. Therefore assessing the principal surrogacy of biomarkers is essentially a missing data problem. In this article, we propose a multiple imputation approach to evaluate candidate principal surrogate markers. The proposed method employs baseline variables to impute the missing potential surrogate markers. The stratum-specific causal treatment effects on the clinical endpoint are then estimated for each imputed dataset and the inference for surrogacy of a biomarker is based on the combined results over multiple imputations. Simulation studies are performed to evaluate the performance of the proposed method and the implementation of the method is illustrated using a vaccine study.

We identified the loci associated with renal scarring risk and protection in affected sib pairs with familial vesicoureteral reflux.A genome-wide analysis of vesicoureteral reflux with high density single nucleotide polymorphisms was conducted in 43 families with 2 or more affected children. A total of 43 probands and 58 affected siblings were included in the analysis. Genomic DNA was extracted from blood or saliva from all patients. All nuclear families had complete parental genotypes and all were Caucasian. Renal scarring was present in 23 of the 43 probands as detected by dimercapto-succinic acid imaging. easyLINKAGE software was used for the genome-wide linkage analysis. A LOD (logarithm [base 10] of odds) score of 3.3 or greater was considered significant evidence of linkage and a LOD score of 2.4 or greater but less than 3.3 was considered suggestive evidence of linkage.Using the affected sib pair method of analysis, a statistically significant linkage peak with a multipoint LOD score of 3.66 for patients without renal scarring was identified on chromosome 11 at 47.97 cM. For the scarring group a peak with a multipoint LOD score of 2.69 was identified on chromosome 17, which provides suggestive evidence of linkage.Our results suggest that a locus on chromosome 11 is associated with protection against renal scarring in patients with vesicoureteral reflux. In addition, a new locus on chromosome 17 may be linked to renal scarring. Our results suggest that multiple genes contribute to the formation of the vesicoureteral reflux phenotype, with patients having a unique susceptibility to renal injury/damage.

Ulrike Boehmer, PhD 1 ; Xiaopeng Miao, MS 2 ; and Al Ozonoff, PhD 2 BACKGROUND: Lesbian, gay, and bisexual populations are not part of cancer surveillance, resulting in scarce information about the cancer survivorship of these populations. To address this information gap, the authors examined the prevalence of cancer survivorship by sexual orientation and cancer survivors’ self-reported health by sexual orientation. METHODS: The authors explored these issues by analyzing pooled data from the California Health Interview survey from 2001, 2003, and 2005. By using descriptive statistics and logistic regressions, they examined the cancer prevalence in men and women by sexual orientation and subsequently compared the self-reported health of male and female cancer survivors by sexual orientation. RESULTS: Among women, the authors found no significant differences in cancer prevalence by sexual orientation, but lesbian and bisexual female cancer survivors had 2.0 and 2.3� the odds of reporting fair or poor health compared with heterosexual female cancer survivors. Among men, we found significant differences in cancer prevalence, with gay men having 1.9� the odds of reporting a cancer diagnosis compared with heterosexual men. There were no differences by sexual orientation in male cancer survivors’ self-reported health. CONCLUSIONS: Our novel findings suggest sex differences in the impact of cancer on lesbian, gay, and bisexual cancer survivors. Lesbian and bisexual cancer survivors need to be targeted by programs and services to assist these cancer survivors in improving their health perceptions, whereas healthcare providers and public health agencies need to be made aware of the higher prevalence of cancer in gay men to prevent future cancers through increased screening and primary prevention. Cancer 2011;117:3796–804. V C 2011 American Cancer Society.

To the Editor—The commentary by Dunning helpfully raises the question about the sensitivity of estimation of the vaccine efficacy (VE) curve to the choice of the baseline immunogenicity predictor (BIP) that is used. In the Zostavax Efficacy and Safety Trial (ZEST) example in our article the VE curve is estimated as a function of 2 binding antibody markers: fold rise and week 6 titer, in each case using baseline titer as the BIP [1]. We apply several statistical methods for estimating the VE curve, each of which separately estimates 2 terms: the disease risk in vaccine recipients conditional on the marker and the disease risk in placebo recipients conditional on the marker, which for a placebo recipient is the marker that s/he would have had if, contrary to fact, s/he had been assigned to receive the vaccine. We call these risks Vrisk(s) and Prisk(s), respectively, for subgroups with marker level s, where the VE curve is VE(s) = 1 – Vrisk(s)/Prisk(s), which measures VE ranging over subgroups defined by the marker level s. Vrisk(s) can be straightforwardly estimated using regression statistical methods without the need for any BIP, because the marker is observed in vaccinated individuals, such that the key issue is estimation of Prisk(s). In our Discussion, we noted that if Vrisk(s) and Prisk(s) are correctly modeled such that valid estimates are obtained, then the VE curve is accurately (unbiasedly) estimated, and this statement holds for any BIP that is reasonably well correlated with the marker, as it is for the ZEST example [1]. Therefore, we recast the question raised by Dunning as “How does a scientist jointly select the BIP and a model for Prisk(s) to obtain a valid estimate of Prisk(s), and how can one evaluate the validity?”

Objective Risk factors for breast, colorectal, and lung cancer are known to be more common among lesbian, gay, and bisexual (LGB) individuals, suggesting they may be more likely to develop these cancers. Our objective was to determine differences in cancer incidence by sexual orientation, using sexual orientation data aggregated at the county level. Methods Data on cancer incidence were obtained from the California Cancer Registry and data on sexual orientation were obtained from the California Health Interview Survey, from which a measure of age-specific LGB population density by county was calculated. Using multivariable Poisson regression models, the association between the age–race-stratified incident rate of breast, lung and colorectal cancer in each county and LGB population density was examined, with race, age group and poverty as covariates. Results Among men, bisexual population density was associated with lower incidence of lung cancer and with higher incidence of colorectal cancer. Among women, lesbian population density was associated with lower incidence of lung and colorectal cancer and with higher incidence of breast cancer; bisexual population density was associated with higher incidence of lung and colorectal cancer and with lower incidence of breast cancer. Conclusions These study findings clearly document links between county-level LGB population density and cancer incidence, illuminating an important public health disparity.

Background Some have suggested gays and lesbians may carry a greater burden of colorectal cancer. To date, individual sexual orientation data are not available in cancer surveillance registries. This prevents an assessment of differences in colorectal cancer incidence and mortality by sexual orientation, using individual-level data. Methods We use an ecological approach to examine differences in colorectal cancer incidence and mortality by county-level sexual orientation data. From the Surveillance, Epidemiology and End Results (SEER) Program we obtain population-based surveillance data on colorectal cancer incidence and mortality from 1996 to 2004. We use Census 2000 data on same-sex partnered households, a proxy of sexual orientation, to derive county-level sexual orientation data. Using multiple regression models, we examined the county-level association of sexual minority density with colorectal cancer incidence and mortality. Results After controlling for race and SES, we identify a significant positive association between greater density of sexual minority men and women and colorectal cancer incidence. With respect to colorectal cancer mortality, we identify a positive association with density of sexual minority men, but not women. Conclusions In the absence of surveillance data on sexual minority individuals, ecological analyses provide estimates of associations at the aggregate level, thereby providing crucial information for follow-up studies.