A protocol for the development of Core Outcome Sets for effectiveness trials and clinical audits in Renal Cell Cancer (R-COS)

The data collection for the interview study is funded by NHS Grampian Endowments, and the costs of the interview transcriptions and eDelphi licences will be paid by the Arcobaleno Cancer Trust. Neither funder had any role in the design of the study. All other parts of the study are currently unfunded. The research team is not personally reimbursed for their time and efforts apart from research input by SD, which is financed by Swedish government funding of clinical research (ALF).Peer reviewedPublisher PD

Survivorship Data in Prostate Cancer:Where Are We and Where Do We Need To Be?

Cancer survivorship was recently identified as a prostate cancer (PCa) research priority by PIONEER, a European network of excellence for big data in PCa. Despite being a research priority, cancer survivorship lacks a clear and agreed definition, and there is a distinct paucity of patient-reported outcome (PRO) data available on the subject. Data collection on cancer survivorship depends on the availability and implementation of (validated) routinely collected patient-reported outcome measures (PROMs). There have been recent advances in the availability of such PROMs. For instance, the European Organisation for Research and Treatment of Cancer Quality of Life Group (EORTC QLG) is developing survivorship questionnaires. This provides an excellent first step in improving the data available on cancer survivorship. However, we propose that an agreed, standardised definition of (prostate) cancer survivorship must first be established. Only then can real-world data on survivorship be collected to strengthen our knowledge base. With more men than ever surviving PCa, this type of research is imperative to ensure that the quality of life of these men is considered as much as their quantity of life. Patient summary: As there are more prostate cancer survivors than ever before, research into cancer survivorship is crucial. We highlight the importance of such research and provide recommendations on how to carry it out. The first step should be establishing agreement on a standardised definition of survivorship. From this, patient-reported outcome measures can then be used to collect important survivorship data.</p

Survivorship data in Prostate Cancer : Where are we and where do we need to be?

Funding/Support and role of the sponsor: PIONEER is funded through the IMI2 Joint Undertaking and is listed under grant agreement 777492. IMI2 receives support from the European Union’s Horizon 2020 research and innovation programme and the European Federation of Pharmaceutical Industries and Associations (EFPIA). The funding bodies played no direct role in this study. The views communicated here are those of PIONEER. Neither the IMI nor the European Union, EFPIA, or any associated partners are responsible for any use that may be made of the information contained herein.Peer reviewedPublisher PD

The need for core outcome sets in renal cancer clinical effectiveness research

Peer reviewedPublisher PD

How Can We Improve Patient-Clinician Communication for Men Diagnosed with Prostate Cancer?

Peer reviewe

Predictive Models for Assessing Patients’ Response to Treatment in Metastatic Prostate Cancer:A Systematic Review

Background and objective: The treatment landscape of metastatic prostate cancer (mPCa) has evolved significantly over the past two decades. Despite this, the optimal therapy for patients with mPCa has not been determined. This systematic review identifies available predictive models that assess mPCa patients’ response to treatment. Methods: We critically reviewed MEDLINE and CENTRAL in December 2022 according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. Only quantitative studies in English were included with no time restrictions. The quality of the included studies was assessed using the PROBAST tool. Data were extracted following the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews criteria. Key findings and limitations: The search identified 616 citations, of which 15 studies were included in our review. Nine of the included studies were validated internally or externally. Only one study had a low risk of bias and a low risk concerning applicability. Many studies failed to detail model performance adequately, resulting in a high risk of bias. Where reported, the models indicated good or excellent performance. Conclusions and clinical implications: Most of the identified predictive models require additional evaluation and validation in properly designed studies before these can be implemented in clinical practice to assist with treatment decision-making for men with mPCa. Patient summary: In this review, we evaluate studies that predict which treatments will work best for which metastatic prostate cancer patients. We found that existing studies need further improvement before these can be used by health care professionals.</p

Predictive Models for Assessing Patients’ Response to Treatment in Metastatic Prostate Cancer:A Systematic Review

Background and objective: The treatment landscape of metastatic prostate cancer (mPCa) has evolved significantly over the past two decades. Despite this, the optimal therapy for patients with mPCa has not been determined. This systematic review identifies available predictive models that assess mPCa patients’ response to treatment. Methods: We critically reviewed MEDLINE and CENTRAL in December 2022 according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. Only quantitative studies in English were included with no time restrictions. The quality of the included studies was assessed using the PROBAST tool. Data were extracted following the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews criteria. Key findings and limitations: The search identified 616 citations, of which 15 studies were included in our review. Nine of the included studies were validated internally or externally. Only one study had a low risk of bias and a low risk concerning applicability. Many studies failed to detail model performance adequately, resulting in a high risk of bias. Where reported, the models indicated good or excellent performance. Conclusions and clinical implications: Most of the identified predictive models require additional evaluation and validation in properly designed studies before these can be implemented in clinical practice to assist with treatment decision-making for men with mPCa. Patient summary: In this review, we evaluate studies that predict which treatments will work best for which metastatic prostate cancer patients. We found that existing studies need further improvement before these can be used by health care professionals.</p

Predictive Models for Assessing Patients’ Response to Treatment in Metastatic Prostate Cancer : A Systematic Review

Peer reviewe

How Can We Improve Patient-Clinician Communication for Men Diagnosed with Prostate Cancer?

Background and objectiveThe ability of health care professionals to communicate with patients compassionately and effectively is crucial for shared decision-making, but little research has investigated patient-clinician communication. As part of PIONEER-an international Big Data Consortium led by the European Association of Urology to answer key questions for men with prostate cancer (PCa), funded through the IMI2 Joint Undertaking under grant agreement 777492- we investigated communication between men diagnosed with PCa and the health care professional(s) treating them across Europe.MethodsWe used the European Organisation for Research and Treatment of Cancer Quality-of-Life Questionnaire-Communication 26, which was shared via the PIONEER and patient organisations on March 11, 2022. We sought men who spoke French, Italian, Spanish, German, Dutch, or English who were diagnosed with PCa and were undergoing or had already received treatment for their PCa.Results and limitationsA total of 372 men reported that they communicated with their clinician during either the diagnostic or the treatment period. Overall, the majority of participants reported positive experiences. However, important opportunities to enhance communication were identified, particularly with regard to correcting misunderstandings, understanding the patient's preferred approach to information presentation, addressing challenging questions, supporting the patient's comprehension of information, attending to the patient's emotional needs, and assessing what information had already been given to patients about their disease and treatment, and how much of it was understood.Conclusions and clinical implicationsThese results help us to identify gaps and barriers to shared treatment decision making. This knowledge will help devise measures to improve patient-health care professional communication in the PCa setting.Patient summaryAs part of the PIONEER initiative, we investigated the communication between men diagnosed with prostate cancer and their health care professionals across Europe. A total of 372 men from six different countries participated in the study. Most participants reported positive experiences, but areas where communication could be improved were identified. These included addressing misunderstandings, tailoring the presentation of information to the patient's preferences, handling difficult questions, supporting emotional needs, and assessing the patient's understanding of their diagnosis and treatment

Predictive Models for Assessing Patients' Response to Treatment in Metastatic Prostate Cancer: A Systematic Review.

Background and objectiveThe treatment landscape of metastatic prostate cancer (mPCa) has evolved significantly over the past two decades. Despite this, the optimal therapy for patients with mPCa has not been determined. This systematic review identifies available predictive models that assess mPCa patients' response to treatment.MethodsWe critically reviewed MEDLINE and CENTRAL in December 2022 according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. Only quantitative studies in English were included with no time restrictions. The quality of the included studies was assessed using the PROBAST tool. Data were extracted following the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews criteria.Key findings and limitationsThe search identified 616 citations, of which 15 studies were included in our review. Nine of the included studies were validated internally or externally. Only one study had a low risk of bias and a low risk concerning applicability. Many studies failed to detail model performance adequately, resulting in a high risk of bias. Where reported, the models indicated good or excellent performance.Conclusions and clinical implicationsMost of the identified predictive models require additional evaluation and validation in properly designed studies before these can be implemented in clinical practice to assist with treatment decision-making for men with mPCa.Patient summaryIn this review, we evaluate studies that predict which treatments will work best for which metastatic prostate cancer patients. We found that existing studies need further improvement before these can be used by health care professionals