Development of a Standardized Set of Patient-centered Outcomes for Advanced Prostate Cancer: An International Effort for a Unified Approach

AbstractBackgroundThere are no universally monitored outcomes relevant to men with advanced prostate cancer, making it challenging to compare health outcomes between populations.ObjectiveWe sought to develop a standard set of outcomes relevant to men with advanced prostate cancer to follow during routine clinical care.Design, setting, and participantsThe International Consortium for Health Outcomes Measurement assembled a multidisciplinary working group to develop the set.Outcome measurements and statistical analysisWe used a modified Delphi method to achieve consensus regarding the outcomes, measures, and case mix factors included.Results and limitationsThe 25 members of the multidisciplinary international working group represented academic and nonacademic centers, registries, and patients. Recognizing the heterogeneity of men with advanced prostate cancer, the group defined the scope as men with all stages of incurable prostate cancer (metastatic and biochemical recurrence ineligible for further curative therapy). We defined outcomes important to all men, such as overall survival, and measures specific to subgroups, such as time to metastasis. Measures gathered from clinical data include measures of disease control. We also identified patient-reported outcome measures (PROMs), such as degree of urinary, bowel, and erectile dysfunction, mood symptoms, and pain control.ConclusionsThe international multidisciplinary group identified clinical data and PROMs that serve as a basis for international health outcome comparisons and quality-of-care assessments. The set will be revised annually.Patient summaryOur international group has recommended a standardized set of patient-centered outcomes to be followed during routine care for all men with advanced prostate cancer

Charting the Depths of Robust Speech Parsing

We describe a novel method for coping with ungrammatical input based on the use of chart-like data structures, which permit anytime processing. Priority is given to deep syntactic analysis. Should this fail, the best partial analyses are selected, according to a shortest-paths algorithm, and assembled in a robust processing phase. The method has been applied in a speech translation project with large HPSG grammars