Balancing benefits and risks in lung cancer therapies: patient preferences for lung cancer treatment alternatives.

Background: In the treatment of Non-Small Cell Lung Cancer (NSCLC) the combination of Immuno- Oncotherapy (IO) and chemotherapy (CT) has been found to be superior to IO or CT alone for patients' survival. Patients and clinicians are confronted with a preference sensitive choice between a more aggressive treatment with a greater negative effect on quality of life versus alternatives that are less effective but have fewer side effects. Objectives: The aims of this study were to: (a) quantify patients' preferences for relevant attributes related to Immuno-Oncotherapy treatment alternatives, and (b) evaluate the maximum acceptable risk (MAR)/Minimum acceptable benefit (MAB) that patients would accept for treatment alternatives. Methods: An online preference survey using discrete-choice experiment (DCE) was completed by NSCLC patients from two hospitals in Italy and Belgium. The survey asked patients' preferences for five patient- relevant treatment attributes. The DCE was developed using a Bayesian D-efficient design. DCE analyses were performed using mixed logit models. Information regarding patient demographics, health literacy, locus of control, and quality of life was also collected. Results: 307 patients (158 Italian, 149 Belgian), stage I to IV, completed the survey. Patients preferred treatments with a higher 5-year survival chance as the most important attribute over all the other attributes. Preference heterogeneity for the attribute weights depended on health literacy, patients' age and locus of control. Patients were willing to accept a substantially increased risks of developing side effects in exchange for the slightest increase (1%) in the chance of surviving at least 5 years from the diagnosis of cancer. Similarly, patients were willing to accept a switch in the mode of administration or complete loss of hair to obtain an increase in survival. Conclusion: In this study, the proportion of respondents who systematically preferred survival over all other treatment attributes was particularly high. Age, objective health literacy and locus of control accounted for heterogeneity in patients' preferences. Evidence on how NSCLC patients trade between survival and other NSCLC attributes can support regulators and other stakeholders on assessing clinical trial evidence and protocols, based on patients' conditions and socio-demographic parameters.

The EU-funded I3LUNG Project: Integrative Science, Intelligent Data Platform for Individualized LUNG Cancer Care With Immunotherapy.

Although immunotherapy (IO) has changed the paradigm for the treatment of patients with advanced non-small cell lung cancers (aNSCLC), only around 30% to 50% of treated patients experience a long-term benefit from IO. Furthermore, the identification of the 30 to 50% of patients who respond remains a major challenge, as programmed Death-Ligand 1 (PD-L1) is currently the only biomarker used to predict the outcome of IO in NSCLC patients despite its limited efficacy. Considering the dynamic complexity of the immune system-tumor microenvironment (TME) and its interaction with the host's and patient's behavior, it is unlikely that a single biomarker will accurately predict a patient's outcomes. In this scenario, Artificial Intelligence (AI) and Machine Learning (ML) are becoming essential to the development of powerful decision-making tools that are able to deal with this high-complexity and provide individualized predictions to better match treatments to individual patients and thus improve patient outcomes and reduce the economic burden of aNSCLC on healthcare systems. I3LUNG is an international, multicenter, retrospective and prospective, observational study of patients with aNSCLC treated with IO, entirely funded by European Union (EU) under the Horizon 2020 (H2020) program. Using AI-based tools, the aim of this study is to promote individualized treatment in aNSCLC, with the goals of improving survival and quality of life, minimizing or preventing undue toxicity and promoting efficient resource allocation. The final objective of the project is the construction of a novel, integrated, AI-assisted data storage and elaboration platform to guide IO administration in aNSCLC, ensuring easy access and cost-effective use by healthcare providers and patients.

Randomised phase II trial (NCT00637975) evaluating activity and toxicity of two different escalating strategies for pregabalin and oxycodone combination therapy for neuropathic pain in cancer patients.

PURPOSE: Neuropathic pain is commonly associated with cancer. Current treatments include combination opioid and adjuvant therapies, but no guidelines are available for dose escalation strategies. This phase II study compared the efficacy and tolerability of two dose escalation strategies for oxycodone and pregabalin combination therapy. METHODS: Patients (N = 75) with oncological neuropathic pain, previously untreated with pregabalin, were recruited in 5 Italian institutions between 2007 and 2010. Patients were randomised to two different dose escalation strategies (arm A; N = 38) oxycodone at a fixed dose with increasing pregabalin doses; (arm B; N = 37) pregabalin at a fixed dose with increasing oxycodone doses. Patients were evaluated from daily diaries and follow-ups at 3, 7, 10, and 14 days after beginning treatment with a numerical rating scale (NRS), neuropathic pain scale (SDN), and well-being scale (ESAS). The primary endpoint was a ≥1/3 reduction in pain (NRS); secondary endpoints included the time to analgesia and adverse effects. The study had a 90% probability of detecting the best strategy for a true difference of at least 15%. RESULTS: More patients in arm A (76%) than arm B (64%) achieved ≥1/3 overall pain reduction even after controlling for baseline factors (gender, baseline pain). Group A reported fewer side effects than group B; constipation 52.8% vs. 66.7%; nausea: 27.8% vs. 44.4%; drowsiness: 44.4% vs. 55.6%; confusion: 16.7% vs. 27.8%; itching: 8.3% vs. 19.4%. CONCLUSIONS: Both strategies effectively controlled neuropathic pain, but according to the adopted selection design arm A is preferable to arm B for pain control. TRIAL REGISTRATION: ClinicalTrials.gov NCT00637975.