Dynamic borrowing of historical controls adjusting for covariates in vaccine efficacy clinical trials

Traditional vaccine efficacy trials usually use fixed designs and often require large sample sizes. Recruiting a large number of subjects can make the trial expensive, long, and difficult to conduct. A possible approach to reduce the sample size and speed up the development is to use historical controls. In this paper, we extend the robust mixture prior (RMP) approach (a well established approach for Bayesian dynamic borrowing of historical controls) to adjust for covariates. The adjustment is done using classical methods from causal inference: inverse probability of treatment weighting, G-computation and double-robust estimation. We evaluate these covariate-adjusted RMP approaches using a comprehensive simulation study and demonstrate their use by performing a retrospective analysis of a prophylactic human papillomavirus vaccine efficacy trial. Adjusting for covariates reduces the drift between current and historical controls, with a beneficial effect on bias, control of type I error and power.

An information-theoretic approach for the assessment of a continuous outcome as a surrogate for a binary true endpoint based on causal inference: Application to vaccine evaluation

Within the causal association paradigm, a method is proposed to assess the validity of a continuous outcome as a surrogate for a binary true endpoint. The methodology is based on a previously introduced information-theoretic definition of surrogacy and has two main steps. In the first step, a new model is proposed to describe the joint distribution of the potential outcomes associated with the putative surrogate and the true endpoint of interest. The identifiability issues inherent to this type of models are handled via sensitivity analysis. In the second step, a metric of surrogacy new to this setting, the so-called individual causal association is presented. The methodology is studied in detail using theoretical considerations, some simulations, and data from a randomized clinical trial evaluating an inactivated quadrivalent influenza vaccine. A user-friendly R package Surrogate is provided to carry out the evaluation exercise.

Putative correlates of protection against shigellosis assessing immunomarkers across responses to S. sonnei investigational vaccine

Shigella spp. are a leading bacterial cause of diarrhea. No widely licensed vaccines are available and there is no generally accepted correlate of protection. We tested a S. sonnei Generalized Modules for Membrane Antigen (GMMA)-based vaccine (1790GAHB) in a phase 2b, placebo-controlled, randomized, controlled human infection model study (NCT03527173) enrolling healthy United States adults aged 18-50 years. We report analyses evaluating immune responses to vaccination, with the aim to identify correlates of risk for shigellosis among assessed immunomarkers. We found that 1790GAHB elicited S. sonnei lipopolysaccharide specific α4β7+ immunoglobulin (Ig) G and IgA secreting B cells which are likely homing to the gut, indicating the ability to induce a mucosal in addition to a systemic response, despite parenteral delivery. We were unable to establish or confirm threshold levels that predict vaccine efficacy facilitating the evaluation of vaccine candidates. However, serum anti-lipopolysaccharide IgG and bactericidal activity were identified as potential correlates of risk for shigellosis.

Effectiveness of maternal immunisation with a three-component acellular pertussis vaccine at preventing pertussis in infants in the United States: Post-hoc analysis of a case-control study using Bayesian dynamic borrowing

BACKGROUND

Immunisation during pregnancy with a tetanus toxoid, reduced diphtheria toxoid and acellular pertussis (Tdap) vaccine can protect infants against pertussis between birth and paediatric vaccination. We aimed to estimate the vaccine effectiveness (VE) of third-trimester pregnancy immunisation with the three-component acellular pertussis (Td3ap) vaccine at preventing pertussis in infants <2 months in the United States (US), to support a label update.

METHODS

We performed a post-hoc sub-analysis of a case-control study conducted in six US Emerging Infections Program Network states between 2011 and 2014. Our analysis included only cases and controls whose mothers were either vaccinated with Td3ap or did not receive any Tdap vaccine. The association between Td3ap maternal immunisation and pertussis in infants was assessed for US data using a frequentist method with conditional logistic regression. A robustified analysis was conducted using Bayesian dynamic borrowing of non-US data, considering a mixing-weighted prior of 90% for historical non-US VE data, and of 10% for a vague prior. VE was estimated as (1-odds ratio) × 100%. Sensitivity analyses accounting for the impact of each non-US study, different mixing weights and missing/ambiguous data were performed.

RESULTS

We included 108 cases and 183 controls. Based on US data, the estimated VE of third-trimester maternal immunisation with Td3ap at preventing pertussis in infants <2 months was 78.0% (95% confidence interval: -38.0; 96.5). VE estimated by Bayesian dynamic borrowing of non-US data (with a 90% weight for historical data) was 83.4% (95% credible interval: 55.7; 92.5); sensitivity analyses produced similar VE estimates.

CONCLUSIONS

Effectiveness of third-trimester pregnancy immunisation with Td3ap at preventing infant pertussis in the US is very likely to be ≥ 50% and is most likely ∼ 80%. Bayesian dynamic borrowing of non-US VE data allowed overcoming the limited power (due to small sample size) of a brand-specific sub-analysis by considering additional evidence.

Vaccine clinical trials with dynamic borrowing of historical controls: Two retrospective studies

Traditional vaccine efficacy trials usually use fixed designs with fairly large sample sizes. Recruiting a large number of subjects requires longer time and higher costs. Furthermore, vaccine developers are more than ever facing the need to accelerate vaccine development to fulfill the public's medical needs. A possible approach to accelerate development is to use the method of dynamic borrowing of historical controls in clinical trials. In this paper, we evaluate the feasibility and the performance of this approach in vaccine development by retrospectively analyzing two real vaccine studies: a relatively small immunological trial (typical early phase study) and a large vaccine efficacy trial (typical Phase 3 study) assessing prophylactic human papillomavirus vaccine. Results are promising, particularly for early development immunological studies, where the adaptive design is feasible, and control of type I error is less relevant.

26. Is There a Correlation Between Reactogenicity and Immune Responses of the Adjuvanted Recombinant Zoster Vaccine (RZV)? A Post-hoc Analysis

Background

RZV (GSK) contains the varicella-zoster virus antigen glycoprotein E (gE) and the adjuvant system AS01B that enhances gE-specific immune responses through stimulating innate immunity. AS01B may contribute to the development of transient local or systemic post-vaccination reactions. A hypothesis that the magnitude of those reactions is predictive of immunogenicity and efficacy (i.e., “no pain, no gain”) remains untested. To evaluate potential correlations between RZV’s reactogenicity and immunogenicity in adults aged ≥ 50 years, a post-hoc analysis was conducted using data from 2 large phase 3 studies (NCT01165177, NCT01165229).

Methods

Reactogenicity was calculated as a single score per symptom (maximum grade recorded over 7 days post-vaccination). A global score obtained by adding each maximum severity for all reported symptoms (multivariate reactogenicity models) and a score for each reactogenicity symptom (univariate reactogenicity models) were estimated.

Results

The analysis included 904 and 147 RZV recipients with completed post-vaccination symptom diary cards and with anti-gE antibody results or cell-mediated immunity (CMI) results, respectively. The global score of reactogenicity post-dose 2 was significantly associated with anti-gE antibody response (p&lt; 0.001, estimate 0.112) although the absolute antibody increase associated with reactogenicity was minimal (1.29-fold increase), while the association with CMI response was not statistically significant (p=0.073, estimate 0.230). There was a weak, but statistically significant association between gE-specific immune responses and the maximum pain post-dose 2 score (p=0.001, estimate 0.041), irrespective of post-vaccination time. Nevertheless, there are observations of immune responses in participants for whom pain was not reported.

Conclusion

A weak but statistically significant correlation was found between injection site pain intensity and immune responses in adult RZV recipients aged ≥ 50 years. However, participants reporting no pain were also able to mount a strong immune response, therefore pain cannot be a surrogate marker to inform on the level of immune response or on likelihood of being protected against herpes zoster.

Funding

GlaxoSmithKline Biologicals SA

Disclosures

Andrea Callegaro, PhD, GSK group of companies (Employee, Shareholder) David O. Willer, PhD, GSK group of companies (Employee, Other Financial or Material Support, Receive GSK shares as part of employment renumeration) Wivine Burny, PhD, GSK group of companies (Employee) Caroline Hervé, PhD, GSK group of companies (Employee) Joon Hyung Kim, MD, GSK group of companies (Employee, Shareholder) myron J. levin, MD, GSK group of companies (Employee, Research Grant or Support) Toufik Zahaf, PhD, GSK group of companies (Employee, Shareholder) Anthony L. Cunningham, F.A.H.M.S., MD, M.B.B.S., B. Med. Sci. (Hons), F.R.A.C.P., F.R.C.P.A., F.A.S.M., GSK group of companies (Grant/Research Support, Advisor or Review Panel member, Speaker’s Bureau) Arnaud Didierlaurent, PhD, GSK group of companies (Other Financial or Material Support, previous employee until 03/2020)Sanofi (Speaker’s Bureau)

1440. Meta-regression Analysis of Worldwide Herpes Zoster Incidence

Background

Many studies have been conducted worldwide to estimate Herpes Zoster (HZ) incidence rates and temporal trends. We systematically reviewed and synthesized studies of HZ incidence rates in the general population using meta-analysis models.

Methods

A random-effects meta-analysis was conducted to estimate HZ incidence from a published worldwide systematic literature review (SLR) including only individuals aged 50 years and older. Meta-regression was used to explore if variability in incidence rates could be explained by a combination of study-specific characteristics in the base model: age, gender, continent and year of data collection. The impact of adding additional covariates: case detection, case definition, study design, incidence type, patient type and latitude to the base model was also assessed.

Results

65 out of 69 studies from the SLR, were included in the analysis: 27 from Europe, 20 from North America, 11 from Asia and 7 from Oceania. There was much variability in study methodology and outcomes. Heterogeneity of incidence rates was greatest across studies conducted in Asia. Meta-analysis results showed that: incidence increased with age; was lower in males compared to females; was lower in Europe and North America compared to Asia and Oceania; and increased from the period prior to 2003 to the period after 2003. The final meta-regression model included continent, year of data collection, gender, age, cubic and quadratic terms for age, as well as an age x gender interaction term. The age x gender interaction suggests that the difference in incidence between males and females is greater in younger ages (e.g. 50-59), whereas in older age groups (e.g. 80+) incidence rates are similar between males and females. None of the additional covariates contributed significantly to the model. It was estimated that 15.5 million HZ cases occurred in 2020 worldwide in individuals aged 50 years and older, which in the absence of vaccination, is projected to increase to 19.8 million by 2030.

Conclusion

The model allows for trends in incidence data to be explored based on influential covariates. Incidence rates were shown to vary by age, gender, continent, and over time.

Funding

GlaxoSmithKline Biologicals SA

Disclosures

Barbara P. Yawn, MD, Msc, ORCID: 0000-0001-7278-5810, The GSK group of companies (Advisor or Review Panel member, Research Grant or Support) Andrea Callegaro, PhD, GSK group of companies (Employee, Shareholder) Kyle Fahrbach, PhD, Evidera (Employee)The GSK group of companies (Other Financial or Material Support, - KF is employed by Evidera that received financial support by the GSK group of companies during the conduct of the study) Binod Neupane, PhD, Evidera (Employee)The GSK group of companies (Other Financial or Material Support, - BN is employed by Evidera that received financial support by the GSK group of companies during the conduct of the study) Hilde Vroling, MSc, The GSK group of companies (Research Grant or Support) Desiree Van Oorschot, Msc, The GSK group of companies (Employee, Shareholder) Desmond Curran, PhD, The GSK group of companies (Employee, Shareholder)

Association Between Immunogenicity and Reactogenicity: A Post Hoc Analysis of 2 Phase 3 Studies With the Adjuvanted Recombinant Zoster Vaccine

A recurrent question is whether transient reactions to vaccines translate into better immune responses. Using clinical data from 2 large phase 3 studies of the recombinant zoster vaccine, we observed a small but statistically significant association between the intensity of a frequent side effect (pain) after vaccination and immune responses to vaccination. However, despite the statistical correlation, the impact on the immune response is so small, and the immune response in individuals without pain already sufficient, that pain cannot be a surrogate marker for an appropriate immune response. Reactogenicity cannot be used to predict immunity after vaccination.

Association Between Hemagglutination Inhibition Antibody Titers and Protection Against Reverse-Transcription Polymerase Chain Reaction–Confirmed Influenza Illness in Children 6–35 Months of Age: Statistical Evaluation of a Correlate of Protection

Background

Data from a randomized controlled efficacy trial of an inactivated quadrivalent influenza vaccine in children 6–35 months of age were used to determine whether hemagglutination inhibition (HI) antibody titer against A/H1N1 and A/H3N2 is a statistical correlate of protection (CoP) for the risk of reverse-transcription polymerase chain reaction (RT-PCR)–confirmed influenza associated with the corresponding strain.

Methods

The Prentice criteria were used to statistically validate strain-specific HI antibody titer as a CoP. The probability of protection was identified using the Dunning model corresponding to a prespecified probability of protection at an individual level. The group-level protective threshold was identified using the Siber approach, leading to unbiased predicted vaccine efficacy (VE). A case-cohort subsample was used for this exploratory analysis.

Results

Prentice criteria confirmed that HI titer is a statistical CoP for RT-PCR–confirmed influenza. The Dunning model predicted a probability of protection of 49.7% against A/H1N1 influenza and 54.7% against A/H3N2 influenza at an HI antibody titer of 1:40 for the corresponding strain. Higher titers of 1:320 were associated with >80% probability of protection. The Siber method predicted VE of 61.0% at a threshold of 1:80 for A/H1N1 and 46.6% at 1:113 for A/H3N2.

Conclusions

The study validated HI antibody titer as a statistical CoP, by demonstrating that HI titer is correlated with clinical protection against RT-PCR–confirmed influenza associated with the corresponding influenza strain and is predictive of VE in children 6–35 months of age.

Clinical Trials Registration

NCT01439360.

Assurance in vaccine efficacy clinical trial design based on immunological responses

The assurance of a future clinical trial is a key quantitative tool for decision-making in drug development. It is derived from prior knowledge (Bayesian approach) about the clinical endpoint of interest, typically from previous clinical trials. In this paper, we examine assurance in the specific context of vaccine development, where early development (Phase 2) is often based on immunological endpoints (e.g., antibody levels), while the confirmatory trial (Phase 3) is based on the clinical endpoint (very large sample sizes and long follow-up). Our proposal is to use the Phase 2 vaccine efficacy predicted by the immunological endpoint (using a model estimated from epidemiological studies) as prior information for the calculation of the assurance.

The intent of students to vaccinate is influenced by cultural factors, peer network, and knowledge about vaccines

Young adults are the future vaccine decision-makers as parents or health-care professionals. To understand their attitudes and behaviors toward vaccination, we conducted a cross-sectional survey of 2079 students attending the University of Antwerp, Belgium and the University of Pisa, Italy. Principal component analysis was used to investigate associations between survey responses and the intent to vaccinate. Vaccination knowledge, attitudes, and behaviors among university students in Italy and Belgium were high. However, only one-half of respondents displayed an intent to vaccinate. High levels of knowledge, positive attitudes, and confidence in vaccines were positively associated with age, higher level of study, being a medical student, a recent vaccination experience, and not knowing trusted persons who did not believe in vaccines. Country of origin was highly correlated with the survey responses and was clustered with lifestyle, family, and data source variables, suggesting a strong modifying effect of culture and family attitudes on how vaccines are perceived in this age-group. Recent meningococcal vaccination campaigns and public discussions around mandatory vaccination in Italy may have influenced these results. We show that the intent to vaccinate was correlated with two main clusters of variables linked to culture (country, family, lifestyle), and to scholarship (knowledge, attitudes, data source) that together influence the behavior of students with respect to vaccination. Our study reinforces previous findings that knowledge about vaccines is key to shaping attitudes and behaviors, but also shows that cultural and lifestyle factors are another platform that could be leveraged in promoting vaccination among young people.

Inference under covariate-adaptive randomization: A simulation study

In clinical trials, several covariate-adaptive designs have been proposed to balance treatment arms with respect to key covariates. Although some argue that conventional asymptotic tests are still appropriate when covariate-adaptive randomization is used, others think that re-randomization tests should be used. In this manuscript, we compare by simulation the performance of asymptotic and re-randomization tests under covariate-adaptive randomization. Our simulation study confirms results expected by the existing theory (e.g. asymptotic tests do not control type I error when the model is miss-specified). Furthermore, it shows that (i) re-randomization tests are as powerful as the asymptotic tests if the model is correct; (ii) re-randomization tests are more powerful when adjusting for covariates; (iii) minimization and permuted blocks provide similar results.

OUP accepted manuscript

Several Bayesian methods have been proposed to borrow information dynamically from historical controls in clinical trials. In this note, we identify key features of the relationship between the first method proposed, the bias-variance method, which is strongly related to the commensurate prior approach, and a more recent and widely used approach called robust mixture priors (RMP). We focus on the two key terms that need to be chosen to define the RMP, namely $w$, the prior probability that the new trial differs systematically from the historical trial, and $s_v^2$, the variance of the vague component of the RMP. The relationship with Pocock's prior reveals that different combinations of these two terms can express similar prior beliefs about the amount of information provided by the historical data. This demonstrates the value of fixing $s_v^2$, e.g., so the vague component is "worth one subject." Prior belief about the relevance of the historical data is then driven by a single value, the prespecified weight $w$.

Transcriptional profiles of adjuvanted hepatitis B vaccines display variable interindividual homogeneity but a shared core signature

The current routine use of adjuvants in human vaccines provides a strong incentive to increase our understanding of how adjuvants differ in their ability to stimulate innate immunity and consequently enhance vaccine immunogenicity. Here, we evaluated gene expression profiles in cells from whole blood elicited in naive subjects receiving the hepatitis B surface antigen formulated with different adjuvants. We identified a core innate gene signature emerging 1 day after the second vaccination and that was shared by the recipients of vaccines formulated with adjuvant systems AS01B, AS01E, or AS03. This core signature associated with the magnitude of the hepatitis B surface-specific antibody response and was characterized by positive regulation of genes associated with interferon-related responses or the innate cell compartment and by negative regulation of natural killer cell–associated genes. Analysis at the individual subject level revealed that the higher immunogenicity of AS01B-adjuvanted vaccine was linked to its ability to induce this signature in most vaccinees even after the first vaccination. Therefore, our data suggest that adjuvanticity is not strictly defined by the nature of the receptors or signaling pathways it activates but by the ability of the adjuvant to consistently induce a core inflammatory signature across individuals.

Knowledge, attitudes and behaviours towards vaccination: a survey of university students in Europe

Background

Immunisation programs are still facing substantial challenges in achieving target coverage rates. This has been attributed to the growing negative individual vaccination attitudes and behaviours. Most of the current studies assessing vaccination knowledge, attitude and beliefs targets adults. However, young people represent future parents and health care professionals. The objective of this study was to investigate vaccination knowledge attitudes and behaviours among university medical and non-medical students in Europe.

Methods

We performed a cross-sectional online survey between April and July 2018. The study participants were students attending different faculties at the University of Antwerp, Belgium and the University of Pisa, Italy. We described sample characteristics. The effect of risk factors was tested with univariate and multivariate logistic regressions.

Results

A total of 2079 participants completed the survey including 873 medical students and 1206 from other faculties. The average of vaccination knowledge, attitudes, and confidence was respectively 5.51 (SD: 1.41), 4.66 (SD: 0.14) and 5.28 (SD: 0.57) on the 6-points scale. Our respondents demonstrated a high level of awareness with respect to their vaccination history. In total, 67.7% (n = 1407) reported to have received at least one vaccine in the previous five years; only 6.0% (n = 35) did not receive any vaccine in the previous 10 years. According to logistic regression analysis Italian students had significantly higher knowledge, attitude and confidence scores than Belgium respondents. Students of medicine scored significantly higher compared to non-medical students.

Conclusions

In order to reduce the gaps in vaccinations knowledge between non-medical and medical students we should plan educational interventions. In this way the number of future sceptical parents could be decreased. Further studies are required to explain the differences between countries.

Key messages

Young adults are the parents and the health care professionals of the future, for this reason their vaccination knowledge attitudes and behaviours should be carefully monitored. European non-medical students have lower vaccinations knowledge, attitudes and confidence compared with medical student. In order to fill these gaps, we should plan educational interventions.

Burden-of-illness vaccine efficacy

In recent years, many vaccines have been developed for the prevention of a variety of diseases. Although the primary objective of vaccination is to prevent disease, vaccination can also reduce the severity of disease in those individuals who develop breakthrough disease. Observations of apparent mitigation of breakthrough disease in vaccine recipients have been reported for a number of vaccine‐preventable diseases such as Herpes Zoster, Influenza, Rotavirus, and Pertussis. The burden‐of‐illness (BOI) score was developed to incorporate the incidence of disease as well as the severity and duration of disease. A severity‐of‐illness score S > 0 is assigned to individuals who develop disease and a score of 0 is assigned to uninfected individuals. In this article, we derive the vaccine efficacy statistic (which is the standard statistic for presenting efficacy outcomes in vaccine clinical trials) based on BOI scores, and we extend the method to adjust for baseline covariates. Also, we illustrate it with data from a clinical trial in which the efficacy of a Herpes Zoster vaccine was evaluated.

Predicted long-term antibody persistence for a tick-borne encephalitis vaccine: results from a modeling study beyond 10 years after a booster dose following different primary vaccination schedules

In tick-borne encephalitis (TBE)-endemic regions, long-term vaccination programs are efficient in preventing the disease. A booster dose of a polygeline-free inactivated TBE vaccine (Encepur Adults, GSK), administered approximately 3 years post-primary vaccination according to 1 of 3 licensed vaccination schedules in adults and adolescents, resulted in antibody persistence for 10 years post-boosting. We used different power-law models (PLMs) to predict long-term persistence of anti-TBE virus neutralization test (NT) antibody titers over a period of 20 years post-booster dose, based on individual antibody NT titers measured for 10 years post-booster vaccination. The PLMs were fitted on pooled data for all vaccine schedules. A mean NT titer of 261 (95% prediction interval: 22–3096), considerably above the accepted threshold of protection (NT titers ≥10), was predicted 20 years post-booster vaccination with TBE vaccine. Our modeled data suggest that the intervals of booster doses could be increased without compromising protection against TBE.

A Th1/IFNγ Gene Signature Is Prognostic in the Adjuvant Setting of Resectable High-Risk Melanoma but Not in Non-Small Cell Lung Cancer

PURPOSE

Immune components of the tumor microenvironment (TME) have been associated with disease outcome. We prospectively evaluated the association of an immune-related gene signature (GS) with clinical outcome in melanoma and non-small cell lung cancer (NSCLC) tumor samples from two phase III studies.

EXPERIMENTAL DESIGN

The GS was prospectively validated using an adaptive signature design to optimize it for the sample type and technology used in phase III studies. One-third of the samples were used as "training set"; the remaining two thirds, constituting the "test set," were used for the prospective validation of the GS.

RESULTS

In the melanoma training set, the expression level of eight Th1/IFNγ-related genes in tumor-positive lymph node tissue predicted the duration of disease-free survival (DFS) and overall survival (OS) in the placebo arm. This GS was prospectively and independently validated as prognostic in the test set. Building a multivariate Cox model in the test set placebo patients from clinical covariates and the GS score, an increased number of melanoma-involved lymph nodes and the GS were associated with DFS and OS. This GS was not associated with DFS in NSCLC, although expression of the Th1/IFNγ-related genes was associated with the presence of lymphocytes in tumor samples in both indications.

CONCLUSIONS

These findings provide evidence that expression of Th1/IFNγ genes in the TME, as measured by this GS, is associated with clinical outcome in melanoma. This suggests that, using this GS, patients with stage IIIB/C melanoma can be classified into different risk groups.

Assessing correlates of protection in vaccine trials: statistical solutions in the context of high vaccine efficacy

Background

The use of correlates of protection (CoPs) in vaccination trials offers significant advantages as useful clinical endpoint substitutes. Vaccines with very high vaccine efficacy (VE) are documented in the literature (VE ≥95%). The rare events (number of infections) observed in the vaccinated groups of these trials posed challenges when applying conventionally-used statistical methods for CoP assessment. In this paper, we describe the nature of these challenges, and propose easy-to-implement and uniquely-tailored statistical solutions for the assessment of CoPs in the specific context of high VE.

Methods

The Prentice criteria and meta-analytic frameworks are standard statistical methods for assessing vaccine CoPs, but can be problematic in high VE cases due to the rare events data available. As a result, lack of fit and the problem of infinite estimates may arise, in the former and latter methods respectively. The use of flexible models within the Prentice framework, and penalized-likelihood methods to solve the issue of infinite estimates can improve the performance of both methods in high VE settings.

Results

We have 1) devised flexible non-linear models to counteract the Prentice framework lack of fit, providing sufficient statistical power to the method, and 2) proposed the use of penalised likelihood approaches to make the meta-analytic framework applicable on randomized subgroups, such as regions. The performance of the proposed methods for high VE cases was evaluated by running simulations.

Conclusions

As vaccines with high efficacy are documented in the literature, there is a need to identify effective statistical solutions to assess CoPs. Our proposed adaptations are straight-forward and improve the performance of conventional statistical methods for high VE data, leading to more reliable CoP assessments in the context of high VE settings.

A note on tests for relevant differences with extremely large sample sizes

A well-known problem in classical two-tailed hypothesis testing is that P-values go to zero when the sample size goes to infinity, irrespectively of the effect size. This pitfall can make the testing of data consisting of large sample sizes potentially unreliable. In this note, we propose to test for relevant differences to overcome this issue. We illustrate the proposed test a on real data set of about 40 million privately insured patients.

MAGE-A3 immunotherapeutic as adjuvant therapy for patients with resected, MAGE-A3-positive, stage III melanoma (DERMA): a double-blind, randomised, placebo-controlled, phase 3 trial

BACKGROUND

Despite newly approved treatments, metastatic melanoma remains a life-threatening condition. We aimed to evaluate the efficacy of the MAGE-A3 immunotherapeutic in patients with stage IIIB or IIIC melanoma in the adjuvant setting.

METHODS

DERMA was a phase 3, double-blind, randomised, placebo-controlled trial done in 31 countries and 263 centres. Eligible patients were 18 years or older and had histologically proven, completely resected, stage IIIB or IIIC, MAGE-A3-positive cutaneous melanoma with macroscopic lymph node involvement and an Eastern Cooperative Oncology Group performance score of 0 or 1. Randomisation and treatment allocation at the investigator sites were done centrally via the internet. We randomly assigned patients (2:1) to receive up to 13 intramuscular injections of recombinant MAGE-A3 with AS15 immunostimulant (MAGE-A3 immunotherapeutic; 300 μg MAGE-A3 antigen plus 420 μg CpG 7909 reconstituted in AS01B to a total volume of 0·5 mL), or placebo, over a 27-month period: five doses at 3-weekly intervals, followed by eight doses at 12-weekly intervals. The co-primary outcomes were disease-free survival in the overall population and in patients with a potentially predictive gene signature (GS-positive) identified previously and validated here via an adaptive signature design. The final analyses included all patients who had received at least one dose of study treatment; analyses for efficacy were in the as-randomised population and for safety were in the as-treated population. This trial is registered with ClinicalTrials.gov, number NCT00796445.

FINDINGS

Between Dec 1, 2008, and Sept 19, 2011, 3914 patients were screened, 1391 randomly assigned, and 1345 started treatment (n=895 for MAGE-A3 and n=450 for placebo). At final analysis (data cutoff May 23, 2013), median follow-up was 28·0 months [IQR 23·3-35·5] in the MAGE-A3 group and 28·1 months [23·7-36·9] in the placebo group. Median disease-free survival was 11·0 months (95% CI 10·0-11·9) in the MAGE-A3 group and 11·2 months (8·6-14·1) in the placebo group (hazard ratio [HR] 1·01, 0·88-1·17, p=0·86). In the GS-positive population, median disease-free survival was 9·9 months (95% CI 5·7-17·6) in the MAGE-A3 group and 11·6 months (5·6-22·3) in the placebo group (HR 1·11, 0·83-1·49, p=0·48). Within the first 31 days of treatment, adverse events of grade 3 or worse were reported by 126 (14%) of 894 patients in the MAGE-A3 group and 56 (12%) of 450 patients in the placebo group, treatment-related adverse events of grade 3 or worse by 36 (4%) patients given MAGE-A3 vs six (1%) patients given placebo, and at least one serious adverse event by 14% of patients in both groups (129 patients given MAGE-A3 and 64 patients given placebo). The most common adverse events of grade 3 or worse were neoplasms (33 [4%] patients in the MAGE-A3 group vs 17 [4%] patients in the placebo group), general disorders and administration site conditions (25 [3%] for MAGE-A3 vs four [<1%] for placebo) and infections and infestations (17 [2%] for MAGE-A3 vs seven [2%] for placebo). No deaths were related to treatment.

INTERPRETATION

An antigen-specific immunotherapeutic alone was not efficacious in this clinical setting. Based on these findings, development of the MAGE-A3 immunotherapeutic for use in melanoma has been stopped.

FUNDING

GlaxoSmithKline Biologicals SA.

Futility for subgroup analyses in the adaptive signature design

Subgroup analyses in clinical trials are becoming increasingly important. In cancer research, more and more targeted therapies are explored from which probably only a portion of the whole population will benefit. An adaptive design for subgroup selection with identification of a subgroup, the adaptive signature design, was proposed in the literature. Unfortunately, measuring and validating the variables defining the subgroup (i.e. biomarkers) can be extremely expensive. For this reason, we propose an extension of this design where subgroup analysis is not performed when the overall results suggest that it is unlikely to achieve statistical significance in the subgroup. Avoiding measuring and validating expensive biomarkers in this case can save resources that could be used on more promising research.

Different Adjuvants Induce Common Innate Pathways That Are Associated with Enhanced Adaptive Responses against a Model Antigen in Humans

To elucidate the role of innate responses in vaccine immunogenicity, we compared early responses to hepatitis B virus (HBV) surface antigen (HBsAg) combined with different Adjuvant Systems (AS) in healthy HBV-naïve adults, and included these parameters in multi-parametric models of adaptive responses. A total of 291 participants aged 18–45 years were randomized 1:1:1:1:1 to receive HBsAg with AS01_B, AS01_E, AS03, AS04, or Alum/Al(OH)₃ at days 0 and 30 (ClinicalTrials.gov: NCT00805389). Blood protein, cellular, and mRNA innate responses were assessed at early time-points and up to 7 days after vaccination, and used with reactogenicity symptoms in linear regression analyses evaluating their correlation with HBs-specific CD4⁺ T-cell and antibody responses at day 44. All AS induced transient innate responses, including interleukin (IL)-6 and C-reactive protein (CRP), mostly peaking at 24 h post-vaccination and subsiding to baseline within 1–3 days. After the second but not the first injection, median interferon (IFN)-γ levels were increased in the AS01_B group, and IFN-γ-inducible protein-10 levels and IFN-inducible genes upregulated in the AS01 and AS03 groups. No distinct marker or signature was specific to one particular AS. Innate profiles were comparable between AS01_B, AS01_E, and AS03 groups, and between AS04 and Alum groups. AS group rankings within adaptive and innate response levels and reactogenicity prevalence were similar (AS01_B ≥ AS01_E > AS03 > AS04 > Alum), suggesting an association between magnitudes of inflammatory and vaccine responses. Modeling revealed associations between adaptive responses and specific traits of the innate response post-dose 2 (activation of the IFN-signaling pathway, CRP and IL-6 responses). In conclusion, the ability of AS01 and AS03 to enhance adaptive responses to co-administered HBsAg is likely linked to their capacity to activate innate immunity, particularly the IFN-signaling pathway.

Testing interaction between treatment and high-dimensional covariates in randomized clinical trials

In this paper, we considered different methods to test the interaction between treatment and a potentially large number (p) of covariates in randomized clinical trials. The simplest approach was to fit univariate (marginal) models and to combine the univariate statistics or p-values (e.g., minimum p-value). Another possibility was to reduce the dimension of the covariates using the principal components (PCs) and to test the interaction between treatment and PCs. Finally, we considered the Goeman global test applied to the high-dimensional interaction matrix, adjusted for the main (treatment and covariates) effects. These tests can be used for personalized medicine to test if a large set of biomarkers can be useful to identify a subset of patients who may be more responsive to treatment. We evaluated the performance of these methods on simulated data and we applied them on data from two early phases oncology clinical trials.

A predictive enrichment procedure to identify potential responders to a new therapy for randomized, comparative controlled clinical studies

To evaluate a new therapy versus a control via a randomized, comparative clinical study or a series of trials, due to heterogeneity of the study patient population, a pre-specified, predictive enrichment procedure may be implemented to identify an "enrichable" subpopulation. For patients in this subpopulation, the therapy is expected to have a desirable overall risk-benefit profile. To develop and validate such a "therapy-diagnostic co-development" strategy, a three-step procedure may be conducted with three independent data sets from a series of similar studies or a single trial. At the first stage, we create various candidate scoring systems based on the baseline information of the patients via, for example, parametric models using the first data set. Each individual score reflects an anticipated average treatment difference for future patients who share similar baseline profiles. A large score indicates that these patients tend to benefit from the new therapy. At the second step, a potentially promising, enrichable subgroup is identified using the totality of evidence from these scoring systems. At the final stage, we validate such a selection via two-sample inference procedures for assessing the treatment effectiveness statistically and clinically with the third data set, the so-called holdout sample. When the study size is not large, one may combine the first two steps using a "cross-training-evaluation" process. Comprehensive numerical studies are conducted to investigate the operational characteristics of the proposed method. The entire enrichment procedure is illustrated with the data from a cardiovascular trial to evaluate a beta-blocker versus a placebo for treating chronic heart failure patients.

Statistical methods for the analysis of clinical trials data containing many zeros: An application in vaccine development

In recent years, many vaccines have been developed for the prevention of a variety of diseases. Many of these vaccines, like the one for herpes zoster, are supposed to act in a multilevel way. Ideally, they completely prevent expression of the virus, but failing that they help to reduce the severity of the disease. A simple approach to analyze these data is the so-called burden-of-illness test. The method assigns a score, say W, equal to 0 for the uninfected and a post-infection outcome X > 0 for the infected individuals. One of the limitations of this test is the potential low power when the vaccine efficacy is close to 0. To overcome this limitation, we propose a Fisher adjusted test where we combine a statistic for infection with a statistic for post-infection outcome adjusted for selection bias. The advantages and disadvantages of different methods proposed in the literature are discussed. We compared the methods via simulations in herpes zoster, HIV, and malaria vaccine trial settings. In addition, we applied these methods to published data on HIV vaccine. The paper ends with some recommendations and conclusions.

Drug-resistance development differs between HIV-1-infected patients failing first-line antiretroviral therapy containing nonnucleoside reverse transcriptase inhibitors with and without thymidine analogues

OBJECTIVES

We evaluated the emergence of drug resistance in patients failing first-line regimens containing one nonnucleoside reverse transcriptase inhibitor (NNRTI) administered with zidovudine (ZDV) + lamivudine (the ZDV group) or non-thymidine analogues (non-TAs) (tenofovir or abacavir, + lamivudine or emtricitabine; the non-TA group).

METHODS

Three hundred HIV-1-infected patients failing a first-line NNRTI-containing regimen (nevirapine, n = 148; efavirenz, n = 152) were included in the analysis. Virological failure was defined as viraemia ≥ 400 HIV-1 RNA copies/mL for the first time at least 6 months after starting the NNRTI-based regimen. For each patient, a genotypic resistance test at failure was available. The presence of drug-resistance mutations in HIV-1 reverse transcriptase was evaluated by comparing patients treated with NNRTI + zidovudine + lamivudine vs. those treated with NNRTI + non-TA.

RESULTS

A total of 208 patients were failing with NNRTI + zidovudine + lamivudine and 92 with NNRTI + non-TA. No significant differences were observed between the non-TA group and the ZDV group regarding the time of virological failure [median (interquartile range): 12 (8-25) vs. 13 (9-32) months, respectively; P = 0.119] and viraemia [median (interquartile range): 4.0 (3.2-4.9) vs. 4.0 (3.3-4.7) log₁₀ copies/mL, respectively; P = 0.894]. Resistance to reverse transcriptase inhibitors (RTIs) occurred at a significant lower frequency in the non-TA group than in the ZDV group (54.3 vs. 75.5%, respectively; P = 0.001). This difference was mainly attributable to a significantly lower prevalence of NNRTI resistance (54.3 vs. 74.0%, respectively; P = 0.002) and of the nucleoside reverse transcriptase inhibitor (NRTI) mutation M184V (23.9 vs. 63.5%, respectively; P < 0.001) in the non-TA group compared with the ZDV group. As expected, the mutation K65R was found only in the non-TA group (18.5%; P < 0.001).

CONCLUSIONS

At first-line regimen failure, a lower prevalence of RTI resistance was found in patients treated with NNRTI + non-TA compared with those treated with NNRTI + zidovudine + lamivudine. These results confirm that the choice of backbone may influence the prevalence of drug resistance at virological failure.

Prevalence of etravirine (ETR)-RAMs at NNRTI failure and predictors of resistance to ETR in a large Italian resistance database (ARCA)

The prevalence of drug resistance associated with the failure of non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimens and the predictors of resistance to Etravirine (ETR) were assessed in 2854 subjects: 39 < 18 (paediatric) and 2815 ≥ 18 (adult) years old. These subjects failed to respond to their current NNRTI treatment, were three-class experienced and had been exposed to NNRTI for ≥3 months. A total of 1827 adult (64.9%) and 32 paediatric subjects (82.1%) harboured the virus with at least one ETR mutation. V179I, Y181C and G190A were the most frequent mutations in both groups. A significantly increased risk of ETR resistance with all three algorithms (Monogram (MGR) >3, Tibotec (TBT) >2 and enhanced MGR (ENH) ≥4) emerged in the paediatric population. Multivariate analysis revealed an increased risk of developing TBT >2 for NNRTI exposure, ENH ≥4 for NNRTI and EFV exposure in paediatric subjects; NVP exposure and higher (≥3.5 log10) HIV-RNA values for all three algorithms in adult subjects, whereas CD4 ≥ 200/μL appeared to be protective. The risk of being ETR resistant was more than doubled for paediatric vs. adult subjects, probably due to a more extensive use of NNRTI and an incomplete virological control.

The Cox shared frailty model with log-skew-normal frailties

Clustered survival data arise when groups of failure times share a common ingredient; typically, they refer to the same individual or individuals with a common factor. When the association between failure times within the same cluster is of interest, statistical methods called frailty models have been used. The frailty is an unobserved random component which affects the risk level, changing from cluster to cluster but shared by all observations within the same cluster. Various probability distributions have been proposed for the frailty term, with special emphasis on the gamma and log-normal distribution. Since adequate modelling of the frailty distribution is essential to properly investigate the dependence structure, we introduce a new class of frailty models with a flexible distribution form. Specifically, we adopt the skew-normal distribution for the log-transformed frailty, leading to an extension of the log-normal model. After presenting the methodology connected to this choice, we illustrate it with a case study of multiple myeloma patients with autologous stem cells transplantation.

Human immunodeficiency virus-1 B and non-B subtypes with the same drug resistance pattern respond similarly to antiretroviral therapy

We analysed the 12-week virological response to protease inhibitor (PI) or non-nucleoside reverse transcriptase inhibitor (NNRTI) therapy in 1108 patients carrying B or non-B human immunodeficiency virus (HIV)-1 subtypes with matched resistance mutation patterns. Response rates were not significantly different for non-B and B subtypes stratified for treatment status (51.5% vs. 41.5% in naïve patients; 46.7% vs. 38.7% in experienced patients) or regimens (46.9% vs. 39.7% with PI; 56.7% vs. 40% with NNRTI). No difference in response was detected in patients harbouring B and non-B subtypes with any resistance profile. Further studies are advisable to fully test this approach on larger datasets.

Allele-sharing statistics using information on family history

When conducting genetic studies for complex traits, large samples are commonly required to detect new genetic factors. A possible strategy to decrease the sample size is to reduce heterogeneity using available information. In this paper we propose a new class of model-free linkage analysis statistics which takes into account the information given by the ungenotyped affected relatives (positive family history). This information is included into the scoring function of classical allele-sharing statistics. We studied pedigrees of affected sibling pairs with one ungenotyped affected relative. We show that, for rare allele common complex diseases, the proposed method increases the expected power to detect linkage. Allele-sharing methods were applied to the symptomatic osteoarthritis GARP study where taking into account the family-history increased considerably the evidence of linkage in the region of the DIO2 susceptibility locus.

Prevalence of mutations and determinants of genotypic resistance to etravirine (TMC125) in a large Italian resistance database (ARCA)

OBJECTIVES

To evaluate whether etravirine (TMC125) might be effective in patients failing therapy with current nonnucleoside reverse transcriptase inhibitors (NNRTIs), we analysed the prevalence of TMC125 mutations and the possible determinants of genotypic resistance to this drug among sequences reported to a large database in Italy [Antiretroviral Resistance Cohort Analysis (ARCA)].

METHODS

We analysed the prevalence of TMC125 resistance-associated mutations (RAMs) and the TMC125 weighted genotypic score (WGS) together with the determinants of genotypic resistance. A total of 5011 sequences from 2955 patients failing NNRTI therapy were evaluated.

RESULTS

Among the sequences in ARCA, 68% had at least one and 9.8% at least three TMC125 RAMs, whereas 31% had a WGS>2. Frequent RAMs were Y181C, G190A, K101E and A98G, whereas V179F, Y181V and G190S appeared in <5% of sequences. Multivariate analysis revealed a higher risk of developing at least three TMC125 RAMs associated with both nevirapine and efavirenz exposure, whereas CD4 counts > or = 200 cells/microL retained their protective effect. An increased risk of WGS>2 was linked to higher HIV RNA values (maximum risk at >5 log(10) copies/mL) and nevirapine exposure; CD4 counts > or = 200 cells/microL were protective.

CONCLUSIONS

The prevalence of TMC125 resistance mutations in the ARCA cohort was 68%. The DUET studies showed that at least three TMC125-associated mutations were required to impair the efficacy of the drug and Y181C/V, V179F and G190S had the greatest effect on response. The prevalence of these mutations among the patients examined in our study was low. However, WGS>2 was found for one-third of our sequences. Previous nevirapine exposure was associated with an increased risk of having WGS>2 (adjusted odds ratio 1.76).

Testing for genetic association in the presence of linkage and gene-covariate interactions

In order to study family-based association in the presence of linkage, we extend a generalized linear mixed model proposed for genetic linkage analysis (Lebrec and van Houwelingen (2007), Human Heredity 64, 5-15) by adding a genotypic effect to the mean. The corresponding score test is a weighted family-based association tests statistic, where the weight depends on the linkage effect and on other genetic and shared environmental effects. For testing of genetic association in the presence of gene-covariate interaction, we propose a linear regression method where the family-specific score statistic is regressed on family-specific covariates. Both statistics are straightforward to compute. Simulation results show that adjusting the weight for the within-family variance structure may be a powerful approach in the presence of environmental effects. The test statistic for genetic association in the presence of gene-covariate interaction improved the power for detecting association. For illustration, we analyze the rheumatoid arthritis data from GAW15. Adjusting for smoking and anti-cyclic citrullinated peptide increased the significance of the association with the DR locus.

New score tests for age-at-onset linkage analysis in general pedigrees

Our aim is to develop methods for mapping genes related to age at onset in general pedigrees. We propose two score tests, one derived from a gamma frailty model with pairwise likelihood and one derived from a log-normal frailty model with approximated likelihood around the null random effect. The score statistics are weighted nonparametric linkage statistics, with weights depending on the age at onset. These tests are correct under the null hypothesis irrespective of the weight used. They are simple, robust, computationally fast, and can be applied to large, complex pedigrees. We apply these methods to simulated data and to the Genetic Analysis Workshop 16 Framingham Heart Study data set. We investigate the time to the first of three events: hard coronary heart disease, diabetes, or death from any cause. We use a two-step procedure. In the first step, we estimate the population parameters under the null hypothesis of no linkage. In the second step, we apply the score tests, using the population parameters estimated in the first step.

Robust age at onset linkage analysis in nuclear families

OBJECTIVE

Standard methods for linkage analysis ignore the phenotype of the parents when they are not genotyped. However, this information can be useful for gene mapping. In this paper we propose methods for age at onset genetic linkage analysis in sibling pairs, taking into account parental age at onset.

METHODS

Two new score statistics are derived, one from an additive gamma frailty model and one from a log-normal frailty model. The score statistics are classical non-parametric linkage (NPL) statistics weighted by a function of the age at onset of the four family members. The weight depends on information from registries (age-specific incidences) and family studies (sib-sib and father-mother correlation).

RESULTS

In order to investigate how age at onset of sibs and their parents affect the information for linkage analysis the weight functions were studied for rare and common disease models, realistic models for breast cancer and human lifespan. We studied the performance of the weighted NPL methods by simulations. As illustration, the score statistics were applied to the GAW12 data. The results show that it is useful to include parental age at onset information in genetic linkage analysis.

Score test for age at onset genetic linkage analysis in selected sibling pairs

A new score statistic is derived, which uses information from registries (age-specific incidences) and family studies (sib-sib marginal correlation) to weight affected sibling pairs according to their age at onset. Age at onset of sibling pairs is modelled by a gamma frailty model. From this model we derive a bivariate survival function, which depends on the marginal survival and on the marginal correlation. The score statistic for linkage is a classical nonparametric linkage (NPL) statistic where the identical by descent sharing is weighted by a particular function of the age at onset data. Since the statistic is based on survival models, it can also be applied to discordant and healthy sibling pairs. Simulation studies show that the proposed method is robust and more powerful than standard NPL methods. As illustration we apply the new score statistic to data from a breast cancer study.

Weighted statistics for aggregation and linkage analysis of human longevity in selected families: the Leiden Longevity Study

Typically long-lived sibling pairs have been collected for linkage analysis of human longevity and information on life span of first-degree relatives is available to assess familial aggregation of life span. We propose a new weighted statistic for aggregation analysis, which tests for a relationship between a family history of excessive survival of the sibships of the long-lived pairs and the survival of their parents and their offspring. For linkage analysis, we derive a new weighted score statistic from a simple gamma frailty model, which assigns more weight to excessive long-lived pairs. We apply the methods to data from the Leiden Longevity Study, which consists of sibling pairs of age 90 years or above and their first-degree relatives. The pairs have been genotyped for microsatellite markers in a candidate region. Association was present between survival within the sibships and survival of the offspring, but not with the parental generation. For linkage analysis, weighting increased the value of the test statistic, but the result was not statistically significant. About the methods we conclude that the statistic for aggregation provides insight into clustering of life span and the statistic for linkage provides a new tool to include demographic information into the analysis.

Combining information from linkage and association methods

Group 12 evaluated approaches to incorporate outside information or otherwise optimize traditional linkage and association analyses. The abundance of available data allowed exploration of identity-by-descent (IBD) estimation, score statistics, formal combination of linkage and association testing, significance estimation, and replication. We observed that IBD estimation can be optimized with a subset of marker data while estimation of inheritance vectors can provide both IBD estimates and a measure of their uncertainty. Score statistics incorporating covariates or combining association and linkage information performed at least as well as standard approaches while requiring less computation time. The formal combination of linkage and association methods may be fruitful, although the nature of the simulated data limited our conclusions. Estimation of significance may be improved through simulation, correction for cryptic relatedness, and the inclusion of prior information. Replication using real data provided consistent results, though the same was not true of simulated data replicates. Overall, we found that increasing the amount of available data limits analyses due to computational constraints and motivates the need to improve methods for the identification of complex-trait genes.

Integrative genomic analysis reveals distinct transcriptional and genetic features associated with chromosome 13 deletion in multiple myeloma

BACKGROUND AND OBJECTIVES

The chromosome 13 deletion (Delta13) is one of the most frequent chromosomal alterations in multiple myeloma (MM). Delta13 is associated with an unfavorable prognosis, although there is increasing agreement that its prognostic relevance must be related to the ploidy status and the presence of different chromosomal translocations. The aim of this study was to provide a comprehensive analysis of the transcriptional features of Delta13 in MM.

DESIGN AND METHODS

Highly purified plasma cells from 80 newly diagnosed MM patients were characterized by means of fluorescence in situ hybridization (FISH) and high-density oligonucleotide microarray for gene expression profiling and chromosomal alterations.

RESULTS

We identified 67 differentially expressed genes in the patients with and without the chromosome 13 deletion, all of which were downregulated in the cases with Delta13: 44 mapped along the whole chromosome 13, seven on chromosome 11 and three on chromosome 19. Functional analyses of the selected genes indicated their involvement in protein biosynthesis, ubiquitination and transcriptional regulation. An integrative genomic approach based on regional analyses of the gene expression data identified distinct chromosomal regions whose global expression modulation could differentiate Delta13-positive cases, in particular the upregulation of 1q21-1q42 and the downregulation of 19p and almost the entire chromosome 11. FISH analyses confirmed the close relationship between Delta13-positivity and the presence of extra copies of 1q21-1q42 (p=6 x 10(-4)) or the absence of chromosome 11 and 19 trisomy (p=5 x 10(-4)).

INTERPRETATION AND CONCLUSIONS

Our results indicate that distinct types of chromosomal aberrations are closely related to the transcriptional profiles of Delta13-positive cases, suggesting that the contribution of Delta13 to the malignancy should be considered together with associated abnormalities.

A gene expression signature associated with survival in metastatic melanoma

Background

Current clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival.

Methods

Forty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM) to identify genes associated with patient survival, and supervised principal components (SPC) to determine survival prediction.

Results

SAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival.

Conclusion

The longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells.

A locally adaptive statistical procedure (LAP) to identify differentially expressed chromosomal regions

MOTIVATION

The systematic integration of expression profiles and other types of gene information, such as chromosomal localization, ontological annotations and sequence characteristics, still represents a challenge in the gene expression arena. In particular, the analysis of transcriptional data in context of the physical location of genes in a genome appears promising in detecting chromosomal regions with transcriptional imbalances often characterizing cancer.

RESULTS

A computational tool named locally adaptive statistical procedure (LAP), which incorporates transcriptional data and structural information for the identification of differentially expressed chromosomal regions, is described. LAP accounts for variations in the distance between genes and in gene density by smoothing standard statistics on gene position before testing the significance of their differential levels of gene expression. The procedure smooths parameters and computes p-values locally to account for the complex structure of the genome and to more precisely estimate the differential expression of chromosomal regions. The application of LAP to three independent sets of raw expression data allowed identifying differentially expressed regions that are directly involved in known chromosomal aberrations characteristic of tumors.

AVAILABILITY

Functions in R for implementing the LAP method are available at http://www.dpci.unipd.it/Bioeng/Publications/LAP.htm