ORIGINAL ARTICLE How to evaluate the effect of pain treatments in cancer patients: Results from a longitudinal outcomes and endpoint Italian cohort study O. Corli 1 , M. Montanari 1 , M.T. Greco 1,2 , C. Brunelli 3,4 , S. Kaasa 4,5,6 A. Caraceni 3,4 , G. Apolone 7 1 Center for the Evaluation and Research on Pain (CERP), Istituto di Ricerche Farmacologiche ‘Mario Negri’, Milan, Italy 2 Department of Clinical Sciences and Community, University of Milan, Milan, Italy 3 Palliative Care Pain Therapy and Rehabilitation Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy 4 European Palliative Care Research Centre (PRC), Trondheim, Norway 5 Norwegian University of Science and Technology (NTNU), Trondheim, Norway 6 University Hospital of Trondheim, Cancer Clinic, Trondheim, Norway 7 Direzione Scientifica, Arcispedale Santa Maria Nuova – IRCCS, Reggio Emilia, Italy Correspondence Oscar Corli E-mail: oscar.corli@marionegri.it Funding sources Unconditional grant by Grunenthal-Italy. Conflicts of interest Dr. Apolone and Dr. Corli received consulting and lecture fees from Grunenthal-Italy. Dr. Kaasa was consultant for Nycomed from 2009 to 2011. Accepted for publication 6 November 2012 doi:10.1002/j.1532-2149.2012.00257.x Abstract Background: Dealing with cancer pain implies assessing the intensity and other attributes of pain and identifying appropriate outcomes and endpoints to evaluate the effect of treatments. Methods: In the context of an observational longitudinal prospective study, 1461 painful cancer patients were evaluated at baseline and weekly over 4 weeks. Four pain intensity (PI) measures (worst, average, least and right now: WP, AP, LP, and PRN), pain relief and patients’ satisfaction with pain treatments were recorded. Starting from these data, we extrapolated the full responder (FR) subjects, whose PI decreased by 2 points, or by 30%, or who obtained a final score of 5 points, according to criteria previously suggested by literature. The receiver operating characteristics (ROC) curve analysis was used to estimate the predictive accuracy. Results: All the PI measures decreased from the initial to final visit: the reduction was 1.9 as WP, 1.3, 0.8 and 1.2 as AP, LP and PRN, respectively. The proportion of FR differed from 47.8% to 88.3% depending on PI measures and the criterion adopted. ROC analysis showed an acceptable accuracy of all endpoints and confirmed the cut-offs recommended by the literature. The best criterion corresponded to a PI absolute value of 4 points when measured as AP. Conclusions: All measures applied seem able to profile the evolution of pain, with some differences. This implies the need of an appropriate choice of outcomes and endpoints according to the goal and objective of the intervention under evaluation. 1. Introduction Cancer patients experience a multitude of symptoms over the course of disease that generally tend to increase in number and severity during the advanced phase (Cleeland, 2000; Tranmer et al., 2003; Cheng et al., 2005; Spichiger et al., 2011). Pain afflicts the majority of cancer patients; a recent review (Van den Beuken-Van Everdingen et al., 2007) estimated that the prevalence of pain varies from 53% to 64%. Other studies (Di Maio et al., 2004; Stromgren et al., 2004) specifically focused on the ter- minal phase found higher rates. Although several guidelines have been available since the second half of 858 Eur J Pain 17 (2013) 858–866 © 2012 European Federation of International Association for the Study of Pain Chapters