Tutorial in Joint Modeling and Prediction: A Statistical Software for Correlated Longitudinal Outcomes, Recurrent Events and a Terminal Event

Extensions in the field of joint modeling of correlated data and dynamic predictions improve the development of prognosis research. The R package frailtypack provides estimations of various joint models for longitudinal data and survival events. In particular, it fits models for recurrent events and a terminal event (frailtyPenal), models for two survival outcomes for clustered data (frailtyPenal), models for two types of recurrent events and a terminal event (multivPenal), models for a longitudinal biomarker and a terminal event (longiPenal) and models for a longitudinal biomarker, recurrent events and a terminal event (trivPenal). The estimators are obtained using a standard and penalized maximum likelihood approach, each model function allows to evaluate goodness-of-fit analyses and provides plots of baseline hazard functions. Finally, the package provides individual dynamic predictions of the terminal event and evaluation of predictive accuracy. This paper presents the theoretical models with estimation techniques, applies the methods for predictions and illustrates frailtypack functions details with examples

Combination Early-Phase Trials of Anticancer Agents in Children and Adolescents

Trials; Anticancer agents; ChildrenEnsayos; Agentes anticancerígenos; NiñosAssajos; Agents anticancerígens; NensPURPOSE There is an increasing need to evaluate innovative drugs for childhood cancer using combination strategies. Strong biological rationale and clinical experience suggest that multiple agents will be more efficacious than monotherapy for most diseases and may overcome resistance mechanisms and increase synergy. The process to evaluate these combination trials needs to maximize efficiency and should be agreed by all stakeholders. METHODS After a review of existing combination trial methodologies, regulatory requirements, and current results, a consensus among stakeholders was achieved. RESULTS Combinations of anticancer therapies should be developed on the basis of mechanism of action and robust preclinical evaluation, and may include data from adult clinical trials. The general principle for combination early-phase studies is that, when possible, clinical trials should be dose- and schedule-confirmatory rather than dose-exploratory, and every effort should be made to optimize doses early. Efficient early-phase combination trials should be seamless, including dose confirmation and randomized expansion. Dose evaluation designs for combinations depend on the extent of previous knowledge. If not previously evaluated, limited evaluation of monotherapy should be included in the same clinical trial as the combination. Randomized evaluation of a new agent plus standard therapy versus standard therapy is the most effective approach to isolate the effect and toxicity of the novel agent. Platform trials may be valuable in the evaluation of combination studies. Patient advocates and regulators should be engaged with investigators early in a proposed clinical development pathway and trial design must consider regulatory requirements. CONCLUSION An optimized, agreed approach to the design and evaluation of early-phase pediatric combination trials will accelerate drug development and benefit all stakeholders, most importantly children and adolescents with cancer

Cost Effectiveness of Modified Fractionation Radiotherapy versus Conventional Radiotherapy for Unresected Non–Small-Cell Lung Cancer Patients

IntroductionModified fractionation radiotherapy (RT), delivering multiple fractions per day or shortening the overall treatment time, improves overall survival for non -small-cell lung cancer (NSCLC) patients compared with conventional fractionation RT (CRT). However, its cost effectiveness is unknown. Therefore, we aimed to examine and compare the cost effectiveness of different modified RT schemes and CRT in the curative treatment of unresected NSCLC patients.MethodsA probabilistic Markov model was developed based on individual patient data from the meta-analysis of radiotherapy in lung cancer (N = 2000). Dutch health care costs, quality-adjusted life years (QALYs), and net monetary benefits (NMBs) were compared between two accelerated schemes (very accelerated RT [VART] and moderately accelerated RT [MART]), two hyperfractionated schemes (using an identical (HRTI) or higher (HRTH) total treatment dose than CRT) and CRT.ResultsAll modified fractionations were more effective and costlier than CRT (1.12 QALYs, €24,360). VART and MART were most effective (1.30 and 1.32 QALYs) and cost €25,746 and €26,208, respectively. HRTI and HRTH yielded less QALYs than the accelerated schemes (1.27 and 1.14 QALYs), and cost €26,199 and €29,683, respectively. MART had the highest NMB (€79,322; 95% confidence interval [CI], €35,478-€133,648) and was the most cost-effective treatment followed by VART (€78,347; 95% CI, €64,635-€92,526). CRT had an NMB of €65,125 (95% CI, €54,663-€75,537). MART had the highest probability of being cost effective (43%), followed by VART (31%), HRTI (24%), HRTH (2%), and CRT (0%).ConclusionImplementing accelerated RT is almost certainly more efficient than current practice CRT and should be recommended as standard RT for the curative treatment of unresected NSCLC patients not receiving concurrent chemo-radiotherapy

Socioeconomic status and its relation with breast cancer recurrence and survival in young women in the Netherlands

BACKGROUND: Associations between socioeconomic status (SES) and breast cancer survival are most pronounced in young patients. We further investigated the relation between SES, subsequent recurrent events and mortality in breast cancer patients < 40 years. Using detailed data on all recurrences that occur between date of diagnosis of the primary tumor and last observation, we provide a unique insight in the prognosis of young breast cancer patients according to SES. METHODS: All women < 40 years diagnosed with primary operated stage I-III breast cancer in 2005 were selected from the nationwide population-based Netherlands Cancer Registry. Data on all recurrences within 10 years from primary tumor diagnosis were collected directly from patient files. Recurrence patterns and absolute risks of recurrence, contralateral breast cancer (CBC) and mortality - accounting for competing risks - were analysed according to SES. Relationships between SES, recurrence patterns and excess mortality were estimated using a multivariable joint model, wherein the association between recurrent events and excess mortality (expected mortality derived from the general population) was included. RESULTS: We included 525 patients. The 10-year recurrence risk was lowest in high SES (18.1%), highest in low SES (29.8%). Death and CBC as first events were rare. In high, medium and low SES 13.2%, 15.3% and 19.1% died following a recurrence. Low SES patients had shorter median time intervals between diagnosis, first recurrence and 10-year mortality (2.6 and 2.7 years, respectively) compared to high SES (3.5 and 3.3 years, respectively). In multivariable joint modeling, high SES was significantly related to lower recurrence rates over 10-year follow-up, compared to low SES. A strong association between the recurrent event process and excess mortality was found. CONCLUSIONS: High SES is associated with lower recurrence risks, less subsequent events and better prognosis after recurrence over 10 years than low SES. Breast cancer risk factors, adjuvant treatment adherence and treatment of recurrence may possibly play a role in this association

Portrait of Ependymoma Recurrence in Children: Biomarkers of Tumor Progression Identified by Dual-Color Microarray-Based Gene Expression Analysis

BACKGROUND: Children with ependymoma may experience a relapse in up to 50% of cases depending on the extent of resection. Key biological events associated with recurrence are unknown. METHODOLOGY/PRINCIPAL FINDINGS: To discover the biology behind the recurrence of ependymomas, we performed CGHarray and a dual-color gene expression microarray analysis of 17 tumors at diagnosis co-hybridized with the corresponding 27 first or subsequent relapses from the same patient. As treatment and location had only limited influence on specific gene expression changes at relapse, we established a common signature for relapse. Eighty-seven genes showed an absolute fold change ≥2 in at least 50% of relapses and were defined as the gene expression signature of ependymoma recurrence. The most frequently upregulated genes are involved in the kinetochore (ASPM, KIF11) or in neural development (CD133, Wnt and Notch pathways). Metallothionein (MT) genes were downregulated in up to 80% of the recurrences. Quantitative PCR for ASPM, KIF11 and MT3 plus immunohistochemistry for ASPM and MT3 confirmed the microarray results. Immunohistochemistry on an independent series of 24 tumor pairs at diagnosis and at relapse confirmed the decrease of MT3 expression at recurrence in 17/24 tumor pairs (p = 0.002). Conversely, ASPM expression was more frequently positive at relapse (87.5% vs 37.5%, p = 0.03). Loss or deletion of the MT genes cluster was never observed at relapse. Promoter sequencing after bisulfite treatment of DNA from primary tumors and recurrences as well as treatment of short-term ependymoma cells cultures with a demethylating agent showed that methylation was not involved in MT3 downregulation. However, in vitro treatment with a histone deacetylase inhibitor or zinc restored MT3 expression. CONCLUSIONS/SIGNIFICANCE: The most frequent molecular events associated with ependymoma recurrence were over-expression of kinetochore proteins and down-regulation of metallothioneins. Metallothionein-3 expression is epigenetically controlled and can be restored in vitro by histone deacetylase inhibitors

Safety and efficacy of plerixafor dose escalation for the mobilization of CD34+ hematopoietic progenitor cells in patients with sickle cell disease: interim results

Gene therapy for sickle cell disease is limited by the yield of hematopoietic progenitor cells that can be harvested for transduction or gene editing. We therefore performed a phase I dose-escalation study of the hematopoietic progenitor cell mobilizing agent plerixafor to evaluate the efficacy and safety of standard dosing on peripheral blood CD34+ cell mobilization. Of 15 patients enrolled to date, only one was chronically transfused and ten were on hydroxyurea. Of eight patients who achieved a CD34+ cell concentration >30 cells/μL, six were on hydroxyurea. There was no clear dose response to increasing plerixafor dosage. There was a low rate of serious adverse events; two patients developed vaso-occlusive crises, at the doses of 80 μg/kg and 240 μg/kg. Hydroxyurea may have contributed to the limited CD34+ mobilization by affecting baseline peripheral blood CD34 counts, which correlated strongly with peak peripheral blood CD34 counts. Plerixafor administration did not induce significant increases in the fraction of activated neutrophils, monocytes, or platelets. However, increased neutrophils positive for activated β2 integrin and Mac-1 were associated with serious adverse events. In summary, plerixafor was well tolerated but did not achieve consistent CD34+ cell mobilization in this cohort of patients, most of whom were being actively treated with hydroxyurea and only one was chronically transfused. The study will continue with escalation of the dose of plerixafor and modification of hydroxyurea administration. Clinicaltrials.gov identifier: NCT02193191

Combination Early-Phase Trials of Anticancer Agents in Children and Adolescents

PURPOSEThere is an increasing need to evaluate innovative drugs for childhood cancer using combination strategies. Strong biological rationale and clinical experience suggest that multiple agents will be more efficacious than monotherapy for most diseases and may overcome resistance mechanisms and increase synergy. The process to evaluate these combination trials needs to maximize efficiency and should be agreed by all stakeholders.METHODSAfter a review of existing combination trial methodologies, regulatory requirements, and current results, a consensus among stakeholders was achieved.RESULTSCombinations of anticancer therapies should be developed on the basis of mechanism of action and robust preclinical evaluation, and may include data from adult clinical trials. The general principle for combination early-phase studies is that, when possible, clinical trials should be dose- and schedule-confirmatory rather than dose-exploratory, and every effort should be made to optimize doses early. Efficient early-phase combination trials should be seamless, including dose confirmation and randomized expansion. Dose evaluation designs for combinations depend on the extent of previous knowledge. If not previously evaluated, limited evaluation of monotherapy should be included in the same clinical trial as the combination. Randomized evaluation of a new agent plus standard therapy versus standard therapy is the most effective approach to isolate the effect and toxicity of the novel agent. Platform trials may be valuable in the evaluation of combination studies. Patient advocates and regulators should be engaged with investigators early in a proposed clinical development pathway and trial design must consider regulatory requirements.CONCLUSIONAn optimized, agreed approach to the design and evaluation of early-phase pediatric combination trials will accelerate drug development and benefit all stakeholders, most importantly children and adolescents with cancer.</p

Combination Early-Phase Trials of Anticancer Agents in Children and Adolescents

PURPOSEThere is an increasing need to evaluate innovative drugs for childhood cancer using combination strategies. Strong biological rationale and clinical experience suggest that multiple agents will be more efficacious than monotherapy for most diseases and may overcome resistance mechanisms and increase synergy. The process to evaluate these combination trials needs to maximize efficiency and should be agreed by all stakeholders.METHODSAfter a review of existing combination trial methodologies, regulatory requirements, and current results, a consensus among stakeholders was achieved.RESULTSCombinations of anticancer therapies should be developed on the basis of mechanism of action and robust preclinical evaluation, and may include data from adult clinical trials. The general principle for combination early-phase studies is that, when possible, clinical trials should be dose- and schedule-confirmatory rather than dose-exploratory, and every effort should be made to optimize doses early. Efficient early-phase combination trials should be seamless, including dose confirmation and randomized expansion. Dose evaluation designs for combinations depend on the extent of previous knowledge. If not previously evaluated, limited evaluation of monotherapy should be included in the same clinical trial as the combination. Randomized evaluation of a new agent plus standard therapy versus standard therapy is the most effective approach to isolate the effect and toxicity of the novel agent. Platform trials may be valuable in the evaluation of combination studies. Patient advocates and regulators should be engaged with investigators early in a proposed clinical development pathway and trial design must consider regulatory requirements.CONCLUSIONAn optimized, agreed approach to the design and evaluation of early-phase pediatric combination trials will accelerate drug development and benefit all stakeholders, most importantly children and adolescents with cancer

Prognosis of cancer patients : input of standard and joint frailty models

La recherche sur le traitement des cancers a évolué durant les dernières années principalement dans une direction: la médecine personnalisée. Idéalement, le choix du traitement doit être basé sur les caractéristiques dupatient et de sa tumeur. Cet objectif nécessite des développements biostatistiques, pour pouvoir évaluer lesmodèles pronostiques, et in fine proposer le meilleur. Dans une première partie, nous considérons le problèmede l’évaluation d’un score pronostique dans le cadre de données multicentriques. Nous étendons deux mesuresde concordance aux données groupées analysées par un modèle à fragilité partagée. Les deux niveaux inter etintra-groupe sont étudiés, et l’impact du nombre et de la taille des groupes sur les performances des mesuresest analysé. Dans une deuxième partie, nous proposons d’améliorer la prédiction du risque de décès en tenantcompte des rechutes précédemment observées. Pour cela nous développons une prédiction issue d’un modèleconjoint pour un événement récurrent et un événement terminal. Les prédictions individuelles proposées sontdynamiques, dans le sens où le temps et la fenêtre de prédiction peuvent varier, afin de pouvoir mettre à jourla prédiction lors de la survenue de nouveaux événements. Les prédictions sont développées sur une série hospitalièrefrançaise, et une validation externe est faite sur des données de population générale issues de registres decancer anglais et néerlandais. Leurs performances sont comparées à celles d’une prédiction issue d’une approchelandmark. Dans une troisième partie, nous explorons l’utilisation de la prédiction proposée pour diminuer ladurée des essais cliniques. Les temps de décès non observés des derniers patients inclus sont imputés en utilisantl’information des patients ayant un suivi plus long. Nous comparons trois méthodes d’imputation : un tempsde survie moyen, un temps échantillonné dans une distribution paramétrique et un temps échantillonné dansune distribution non-paramétrique des temps de survie. Les méthodes sont comparées en termes d’estimationdes paramètres (coefficient et écart-type), de risque de première espèce et de puissance.Research on cancer treatment has been evolving for last years in one main direction: personalised medicine. Thetreatment choice must be done according to the patients’ and tumours’ characteristics. This goal requires somebiostatistical developments, in order to assess prognostic models and eventually propose the best one. In a firstpart, we consider the problem of assessing a prognostic score when multicentre data are used. We extended twoconcordance measures to clustered data in the context of shared frailty model. Both the between-cluster andthe within-cluster levels are studied, and the impact of the cluster number and size on the performance of themeasures is investigated. In a second part, we propose to improve the prediction of the risk of death accountingfor the previous observed relapses. For that, we develop predictions from a joint model for a recurrent event anda terminal event. The proposed individual prediction is dynamic, both the time and the horizon of predictioncan evolve, so that the prediction can be updated at each new event time. The prediction is developed ona French hospital series, and externally validated on population-based data from English and Dutch cancerregistries. Its performances are compared to those of a landmarking approach. In a third part, we explore theuse of the proposed prediction to reduce the clinical trial duration. The non-observed death times of the lastincluded patients are imputed using the information of the patients with longer follow-up. We compared threemethods to impute the data: a survival mean time, a time sampled from the parametric distribution and atime sampled from a non-parametric distribution of the survival times. The comparison is made in terms ofparameters estimation (coefficient and standard-error), type-I error and power

Pronostic en cancérologie : apport des modèles à fragilité standards et conjoints

Research on cancer treatment has been evolving for last years in one main direction: personalised medicine. Thetreatment choice must be done according to the patients’ and tumours’ characteristics. This goal requires somebiostatistical developments, in order to assess prognostic models and eventually propose the best one. In a firstpart, we consider the problem of assessing a prognostic score when multicentre data are used. We extended twoconcordance measures to clustered data in the context of shared frailty model. Both the between-cluster andthe within-cluster levels are studied, and the impact of the cluster number and size on the performance of themeasures is investigated. In a second part, we propose to improve the prediction of the risk of death accountingfor the previous observed relapses. For that, we develop predictions from a joint model for a recurrent event anda terminal event. The proposed individual prediction is dynamic, both the time and the horizon of predictioncan evolve, so that the prediction can be updated at each new event time. The prediction is developed ona French hospital series, and externally validated on population-based data from English and Dutch cancerregistries. Its performances are compared to those of a landmarking approach. In a third part, we explore theuse of the proposed prediction to reduce the clinical trial duration. The non-observed death times of the lastincluded patients are imputed using the information of the patients with longer follow-up. We compared threemethods to impute the data: a survival mean time, a time sampled from the parametric distribution and atime sampled from a non-parametric distribution of the survival times. The comparison is made in terms ofparameters estimation (coefficient and standard-error), type-I error and power.La recherche sur le traitement des cancers a évolué durant les dernières années principalement dans une direction: la médecine personnalisée. Idéalement, le choix du traitement doit être basé sur les caractéristiques dupatient et de sa tumeur. Cet objectif nécessite des développements biostatistiques, pour pouvoir évaluer lesmodèles pronostiques, et in fine proposer le meilleur. Dans une première partie, nous considérons le problèmede l’évaluation d’un score pronostique dans le cadre de données multicentriques. Nous étendons deux mesuresde concordance aux données groupées analysées par un modèle à fragilité partagée. Les deux niveaux inter etintra-groupe sont étudiés, et l’impact du nombre et de la taille des groupes sur les performances des mesuresest analysé. Dans une deuxième partie, nous proposons d’améliorer la prédiction du risque de décès en tenantcompte des rechutes précédemment observées. Pour cela nous développons une prédiction issue d’un modèleconjoint pour un événement récurrent et un événement terminal. Les prédictions individuelles proposées sontdynamiques, dans le sens où le temps et la fenêtre de prédiction peuvent varier, afin de pouvoir mettre à jourla prédiction lors de la survenue de nouveaux événements. Les prédictions sont développées sur une série hospitalièrefrançaise, et une validation externe est faite sur des données de population générale issues de registres decancer anglais et néerlandais. Leurs performances sont comparées à celles d’une prédiction issue d’une approchelandmark. Dans une troisième partie, nous explorons l’utilisation de la prédiction proposée pour diminuer ladurée des essais cliniques. Les temps de décès non observés des derniers patients inclus sont imputés en utilisantl’information des patients ayant un suivi plus long. Nous comparons trois méthodes d’imputation : un tempsde survie moyen, un temps échantillonné dans une distribution paramétrique et un temps échantillonné dansune distribution non-paramétrique des temps de survie. Les méthodes sont comparées en termes d’estimationdes paramètres (coefficient et écart-type), de risque de première espèce et de puissance