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BACKGROUND: PAOLA-1/ENGOT-ov25 (NCT02477644) demonstrated a significant progression-free survival (PFS) benefit with maintenance olaparib plus bevacizumab versus placebo plus bevacizumab in newly diagnosed, advanced ovarian cancer. We report the prespecified main second progression-free survival (PFS2) analysis for PAOLA-1. METHODS: This randomised, double-blind, phase III trial was conducted in 11 countries. Eligible patients had newly diagnosed, advanced, high-grade ovarian cancer and were in response after first-line platinum-based chemotherapy plus bevacizumab. Patients were randomised 2:1 to olaparib (300 mg twice daily) or placebo for up to 24 months; all patients received bevacizumab (15 mg/kg every 3 weeks) for up to 15 months. Primary PFS end-point was reported previously. Time from randomisation to second disease progression or death was a key secondary end-point included in the hierarchical-testing procedure. RESULTS: After a median follow-up of 35.5 months and 36.5 months, respectively, median PFS2 was 36.5 months (olaparib plus bevacizumab) and 32.6 months (placebo plus bevacizumab), hazard ratio 0.78; 95% confidence interval (CI) 0.64-0.95; P = 0.0125. Median time to second subsequent therapy or death was 38.2 months (olaparib plus bevacizumab) and 31.5 months (placebo plus bevacizumab), hazard ratio 0.78; 95% CI 0.64-0.95; P = 0.0115. Seventy-two (27%) patients in the placebo plus bevacizumab group received a poly(ADP-ribose) polymerase inhibitor as first subsequent therapy. No new safety signals were observed for olaparib plus bevacizumab. CONCLUSION: In newly diagnosed, advanced ovarian cancer, maintenance olaparib plus bevacizumab provided continued benefit beyond first progression, with a significant PFS2 improvement and a time to second subsequent therapy or death delay versus placebo plus bevacizumab. ispartof: EUROPEAN JOURNAL OF CANCER vol:174 pages:221-231 ispartof: location:England status: published

Retail is changing as technology is growing. The traditional way of shopping has evolved thanks to mobile devices, and retailers are struggling to avoid customers’ attrition. Customers are immersed in a seamless omnichannel experience that allows them to switch from channel to channel and search for the most convenient way of shopping at all times. In this context, retailers have to compete not only with other brands but also with other channels of the same brand, and this situation makes it difficult for them to develop new ways of engaging the customers and create loyalty programs to make the most of their investments in the stores. Effective product recommendation has become one of the key selling strategies employed everywhere, from brick-and-mortar stores to omnichannel retail, in order to increase sales and revenues and to increase repeat purchases from the same retail store and brand. The goal of this PhD Thesis is divided into two interrelated purposes: (1) to identify which are the trigger factors that motivate customers on the choice of each shopping channel and (2) to provide retailers with an algorithm that optimises the mix of recommended products in a brick-and-mortar store so as to provide the customer with an additional experience and engage them to the retail store. To reach those objectives we have analysed the different trends in the purchase process online and offline under the multichannel or omnichannel strategies. The methodology combines an exhaustive revision of academic literature about omnichannel strategies as well as reports from specialised consultant companies so as to define the trends and the factors that motivate customers towards one or another shopping path. As for the second study, with the goal of maximizing the total attractiveness value for the visiting customers to retail shops, and considering a multi-period tie horizon, we have studied how to determine an assortment of products to be included in display tables. In order to deal with the underlying optimization problem, a biased-randomized heuristic is proposed. In a first stage, it constructs an initial feasible solution. In a second stage, this initial solution is improved by employing a local search mechanism. A set of instances has been generated to test the approach. Different product-selection methodologies have been tested to illustrate the potential benefits of the proposed algorithm. The findings of the first study indicate that there are common trigger factors for every shopping channel and for every stage of the purchase path. As regards the second study, recommending a set of correlated and attractive products on retail display tables that vary often is a promising way to engage customers with such an attractive experience. The result of this research will allow retailers to face omnichannel strategies in such a way that they manage to engage and retain customers avoiding attrition and optimising their investments. Being able to know what is the best selection of products that best appeal to customers, provides a rationalization of the stock shown at every store and increases productivity of the employees in charge of such stock decisions. El comerç minorista està canviant a mesura que la tecnologia està creixent. La forma tradicional de comprar ha evolucionat gràcies als dispositius mòbils, i els minoristes estan lluitant per evitar la pèrdua de clients. Els clients estan immersos en una experiència omnicanal perfecta que els permet anar de canal en canal i buscar la forma més convenient de comprar en tot moment. En aquest context, els minoristes han de competir no només amb altres marques, sinó també amb altres canals de la mateixa marca, i aquesta situació els dificulta desenvolupar noves formes d'involucrar els clients i crear programes de lleialtat per aprofitar al màxim les seves inversions en les botigues. La recomanació efectiva de productes s'ha convertit en una de les estratègies de venda clau emprades en el comerç en general per augmentar les vendes i ingressos i augmentar les compres repetides a la mateixa botiga i marca. L'objectiu d'aquesta tesi doctoral es divideix en dos propòsits interrelacionats: (1) identificar quins són els factors desencadenants que motiven als clients en l'elecció de cada canal de compres i (2) proporcionar als minoristes un algoritme que optimitzi la combinació de productes recomanats en una botiga física per a proporcionar al client una experiència addicional i atreure'ls a la botiga. Per assolir aquests objectius, hem analitzat les diferents tendències en el procés de compra tant en un entorn físic com virtual sota les estratègies multicanal o omnicanal. La metodologia combina una revisió exhaustiva de la literatura acadèmica sobre estratègies omnicanal, així com informes d'empreses consultores especialitzades per a definir les tendències i els factors que motiven als clients cap a una o altra via de compra. Pel que fa al segon estudi, amb l'objectiu de maximitzar el valor d'atractiu total per als clients visitants a les botigues minoristes, i considerant un horitzó d'enllaç de múltiples períodes, hem estudiat com determinar un assortiment de productes per incloure a les taules d'exposició de productes. Per abordar el problema d'optimització subjacent, es proposa una heurística aleatòria esbiaixada. En una primera etapa, es construeix una solució factible inicial. En una segona etapa, aquesta solució inicial es millora en emprar un mecanisme de cerca local. S'han generat un conjunt d'instàncies per provar l'enfocament. S'han provat diferents metodologies de selecció de productes per a il·lustrar els beneficis potencials de l'algoritme proposat. Els resultats del primer estudi indiquen que hi ha factors desencadenants comuns per a cada canal de compres i per a cada etapa de la ruta de compra. Pel que fa al segon estudi, recomanar un conjunt de productes correlacionats i atractius a les taules expositores que varien sovint és una forma prometedora d'atraure els clients a la botiga física. El resultat d'aquesta investigació permetrà als minoristes dissenyar estratègies omnicanal de tal manera que aconsegueixin atreure i retenir els clients evitant la pèrdua de clients i optimitzant les seves inversions. Ser capaç de saber quina és la millor selecció de productes que millor atrau els clients, proporciona una racionalització de l'estoc que es mostra en cada botiga i augmenta la productivitat dels empleats a càrrec d'aquestes decisions d'estoc.