scholarly journals Which patient-reported outcomes shall we use in hand surgery?

2019 ◽  
Vol 45 (1) ◽  
pp. 5-11 ◽  
Author(s):  
Miriam Marks

Nowadays, the use of patient-reported outcome measures to monitor a treatment effect in daily practice or to quantify study outcomes is indispensable. In hand surgery, there is a wide variety available. This article provides an overview about the most common hand-specific, upper-extremity specific and general quality of life patient-reported outcome measurement instruments with adequate psychometric properties. A checklist and a decision tree are provided for choosing the appropriate instrument when evaluating patients with hand conditions.

2019 ◽  
Vol 45 (1) ◽  
pp. 12-18 ◽  
Author(s):  
Roberto S. Rosales ◽  
Isam Atroshi

This article presents the methodological requirements for clinical examination and patient-reported outcomes measurements. The assessment of any measurement for clinical research in hand surgery is difficult. A method of measuring a criterion could be 100% reliable but 100% invalid. Bias may be present in our assessment if we do not take into account the methodological requirements related to reliability, validity, and responsiveness of our measures. Reliability refers to intra-observer agreement, inter-observer agreement, or agreement between two methods of assessment, and, for patient-reported measures, internal consistency and test–retest reliability. Validity is the capability of a clinical method to measure what it proposes to measure. Assessing validity involves comparing a measure with one or more other measures, and, if possible, with a reference standard criterion. Responsiveness is the ability to detect important clinical change. The Consensus-based Standards for the Selection of Health Measurement Instruments provides the standards required for design and recommended statistical analyses of patient-reported outcome measures.


2019 ◽  
Vol 4 (1) ◽  
pp. 8-15 ◽  
Author(s):  
Kathryn Yorkston ◽  
Carolyn Baylor

Patient-reported outcome measures contain information that comes directly from the patient without interpretation by anyone else. These measures are an important part of a clinicians' arsenal of assessment approaches and are critical in the development of patient-centered approaches to intervention. In this introduction to patient-reported outcome measurement tools, a history is provided of this approach to measurement and its place within the context of clinical research and practice. The process of instrument development and application will be reviewed, along with examples of measurement tools from the field of neurological communication disorders. This introduction is supplemented by references that provide interested readers with more detailed information.


2014 ◽  
Vol 20 (3) ◽  
pp. 165-171 ◽  
Author(s):  
Glyn Lewis ◽  
Helen Killaspy

SummaryIt has been argued that the routine use of patient-reported outcome measures (PROMs) should be encouraged in order to improve the quality of services and even to determine payment. Clinician-rated outcome measures (CROMs), patient-reported experience measures (PREMs) and process measures also should be considered in evaluating healthcare quality. We discuss difficulties that the routine use of outcome measures might pose for psychiatric services. When outcome and experience measures are used to evaluate services they are difficult to interpret because of differences in case mix and regression to the mean. We conclude that PROMs and CROMs could be useful for monitoring the progress of individuals and that clinical audit still has an important role to play in improving the quality of services.LEARNING OBJECTIVESUnderstand the difference between process measurement and outcome measurement.Understand the limitation of using outcome measures to assess and promote quality of services.Understand the difficulties in assessing the psychometric properties and validity of outcome measures.


2021 ◽  
Author(s):  
Pimrapat Gebert ◽  
Daniel Schindel ◽  
Johann Frick ◽  
Liane Schenk ◽  
Ulrike Grittner

Abstract BackgroundPatient-reported outcome measures (PROMs) are commonly used and are surrogates for clinical outcomes in cancer research. In the research setting of very severe diseases such as cancer, it is difficult to avoid the problem of incomplete questionnaires from drop-out or missing data due to patients who deceased during observation period. We aimed to explore patient characteristics and patient-reported outcomes associated with the time-to-dropout. MethodsIn the Oncological Social Care Project (OSCAR) study the condition of participants was assessed four times within 12 months (t0: baseline, t1: 3 months, t2: 6 months, and t3: 12 months) by validated PROMs. We performed competing-risks regression based on Fine and Gray’s proportional sub-distribution hazards model for exploring factors associated with time-to-dropout. Death was considered as competing risk. ResultsThree hundred sixty-two participants were analyzed in the study. 193 (53.3%) completed follow-up at 12 months, 67 (18.5%) patients dropped out, and 102 patients (28.2%) died during the study period. Poor subjective social support was related to higher risk for drop-out (SHR=2.10; 95%CI: 1.01 – 4.35). Lower values in health-related quality of life were related to drop-out and death. The subscales global health status/QoL, role functioning, physical functioning, and fatigue symptom in the EORTC QLQ-C30 were key characteristics associated with early drop-out.ConclusionSeverely affected cancer patients with poor social support and poor quality of life seem more likely to drop out of studies compared to patients with higher levels of social support and quality of life. This should be considered when planning studies assessing cancer patients. Methods to monitor drop-outs timely and handle missing outcomes might be used. Results of such studies have to be interpreted with caution in light of the particular drop-out mechanisms.


Cancers ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2487
Author(s):  
Ramez Kouzy ◽  
Joseph Abi Jaoude ◽  
Daniel Lin ◽  
Nicholas D. Nguyen ◽  
Molly B. El Alam ◽  
...  

Pancreatic cancer and its treatment often dramatically impact patients’ quality of life (QoL). Given this, as well as increased focus on QoL measures in clinical oncology, there has been a rise in the number of instruments that measure patient-reported outcomes (PROs). In this review, we describe the landscape of different PRO instruments pertaining to pancreatic cancer, with specific emphasis on PRO findings related to pancreatic cancer patients receiving radiotherapy (RT). Twenty-five of the most commonly utilized PROs are compared in detail. Notably, most of the PRO tools discussed are not specific to pancreatic cancer but are generic and have been used in various malignancies. Published findings concerning PROs in pancreatic cancer involving RT are also extracted and summarized. Among the measures used, the European Organization for Research and Treatment Cancer QLQ-C30 was the most commonly utilized. We recommend a careful selection of PRO measures in clinical pancreatic cancer research and care and encourage the use of a combination of symptom-specific and global QoL tools to more fully capture patients’ perspectives.


2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 345.1-346
Author(s):  
A. Berti ◽  
G. Boleto ◽  
P. A. Merkel ◽  
G. Tomasson ◽  
S. Monti ◽  
...  

Background:The OMERACT Vasculitis Working Group has defined a Core Domain Set of outcome measures for ANCA-associated vasculitis (AAV). However, the psychometric properties of available outcome measurement instruments in AAV, an essential consideration when choosing among instruments, have not been summarized.Objectives:To systematically review and summarize the psychometric properties of outcome measurement instruments used in AAV.Methods:A comprehensive search of several databases (Medline, EMBASE, Cochrane, Scopus, among others) from inception to July 14, 2020 and without language limitations was conducted. Articles were included if they covered psychometric properties of instruments used in AAV (granulomatosis with polyangiitis, GPA; microscopic polyangiitis, MPA; eosinophilic granulomatosis with polyangiitis, EGPA); articles encompassing other systemic vasculitides and not presenting the data for AAV separately were excluded. Following the COSMIN and OMERACT frameworks, different psychometric properties (validity, inter- and intra-observer reliability, sensitivity to change, and feasibility) of outcome measurement instruments used in AAV were assessed. Risk of bias was assessed according to the COSMIN checklist.Results:From 2505 articles identified, 20 met the predefined criteria. Three were identified as development studies, 14 were validation studies, and 3 pursued both objectives.These studies provided information on 16 instruments: 8 assessing disease activity, 1 assessing disease damage, 3 assessing patient-reported outcome, 4 assessing function (Figure 1). Overall, a few psychometric properties have been considered in each study, ranging from one to five. Most of the instruments were tested in GPA only (n=7), followed by AAV as a group (GPA, MPA and EGPA; n=5), MPA and GPA (n=3), and EGPA only (n=1). Sample sizes of the studies ranged between 27 and 626 patients. The studies with a higher risk of bias, according to COSMIN definitions, were those assessing RAPID3, MVIA, ENT/GPA DAS, and ODSS.There was a wide heterogeneity of the psychometric proprieties assessed for each instrument. Validity was the most frequently assessed domain in 88% of the instruments, and few properties other than construct validity were reported (Figure 1).Within each domain, BVAS/WG for activity, VDI for damage, AAV-PRO for patient-reported outcomes, and ODSS for function were the instruments with more psychometric features assessed. For the disease activity domain, BVAS/WG showed a good validity having the highest correlation with physician global assessment (r=0.90), a good reliability (intra-observer ICC=0.62; inter-observer ICC=0.97), and good feasibility and responsiveness. For disease damage, VDI showed moderate validity (correlations with BVAS/WG at 5-year with r=0.20 and BVAS/WG at 1-year with r=0.40) and good feasibility. Among patient-reported outcomes, AAV-PRO had the best performance in terms of validity (construct validity: correlations of the 6 disease domains and EQ-5D-5L, with r ranging between -0.78 and -0.55; discriminating validity between active disease versus remission of the 6 disease domains, p<0.0001 for all comparisons). The performance of instruments assessing function domain was low-to-moderate.Conclusion:Sixteen instruments covering the OMERACT domains of disease activity, damage, patient-reported outcome, and function had their psychometric properties assessed in the study of AAV. The majority were developed or validated for GPA only or AAV as a group. Overall, validity was the domain most frequently assessed. BVAS/WG, VDI, AAV-PRO, and ODSS were the instruments with more psychometric features assessed. More rigorous studies aimed at estimating a wider range of psychometric properties in larger numbers of patients with AAV are warranted.References:[1]Castrejon I, et al. Clin Exp Rheumatol. 2015[2]Merkel PA, Journal of Rheumatology, July 2011Disclosure of Interests:None declared


2020 ◽  
Author(s):  
Pimrapat Gebert ◽  
Daniel Schindel ◽  
Johann Frick ◽  
Liane Schenk ◽  
Ulrike Grittner

Abstract BackgroundPatient-reported outcome measures are commonly used and are surrogates for clinical outcomes in cancer research. In the research setting of very severe diseases such as cancer, it is difficult to avoid the problem of incomplete questionnaires from drop-out or missing data due to patients who deceased during observation period. We aimed to explore patient characteristics and patient-reported outcomes associated with the time-to-dropout. MethodsIn the Oncological Social Care Project (OSCAR) study the condition of participants was assessed four times within 12 months (t0: baseline, t1: 3 months, t2: 6 months, t3:12 months) by validated patient-reported outcome measures. We performed competing-risks regression based on Fine and Gray’s proportional sub-distribution hazards model for exploring factors associated with time-to-dropout. Death was considered a competing risk. ResultsThree hundred sixty-two participants were analyzed in the study. 193 (53.3%) completed follow-up at 12 months, 67 (18.5%) patients dropped out, and 102 patients (28.2%) died during the study period. Poor subjective social support was related to higher risk for drop-out (SHR=2.10; 95%CI: 1.01 – 4.35). Lower values in quality of life (EORTC QLQ-C30) were related to drop-out and death. The subscales global health status/QoL, role functioning, physical functioning, and fatigue symptom were key characteristics associated with drop-out.ConclusionSeverely affected cancer patients with poor social support and poor quality of life seem more likely to drop out of studies compared to patients with higher levels of social support and quality of life. This should be considered when planning studies assessing cancer patients. Methods to monitor drop-outs timely and handle missing outcomes might be used. Results of such studies have to be interpreted with caution in light of the particular drop-out mechanisms.


Author(s):  
Laure Gossec ◽  
Tania Gudu ◽  
Maarten de Wit

Psoriatic arthritis (PsA) is a chronic, potentially severe disease with an important impact on the lives of people who have this disease. The impact of PsA is wide-reaching, and both physical but also mental aspects of quality of life can be modified by this disease. Thus, the measurement of the patient’s status rests in part, on the assessment of patient-reported outcomes, i.e. questionnaires to assess different aspects of life. In the present chapter, we will discuss the impact of the disease from a qualitative point of view, and review different patient-reported questionnaires which are either specific to PsA, or generic, and which are used to assess people with PsA.


2018 ◽  
Vol 212 (1) ◽  
pp. 4-5 ◽  
Author(s):  
Jed Boardman

SummaryPatient-reported outcome measures (PROMs) are self-rated, but may not take in other aspects of the patient's perspective, such as the inclusion of domains that reflect service-user priorities. The clinician's view still has priority, although this situation has shifted in recent years. The Recovering Quality of Life (ReQoL) offers an advance in this area.Declaration of interestNone.


2021 ◽  
Author(s):  
Pimrapat Gebert ◽  
Daniel Schindel ◽  
Johann Frick ◽  
Liane Schenk ◽  
Ulrike Grittner

Abstract BackgroundPatient-reported outcome measures (PROMs) are commonly used and are surrogates for clinical outcomes in cancer research. In the research setting of very severe diseases such as cancer, it is difficult to avoid the problem of incomplete questionnaires from drop-out or missing data due to patients who deceased during observation period. We aimed to explore patient characteristics and patient-reported outcomes associated with the time-to-dropout. MethodsIn the Oncological Social Care Project (OSCAR) study the condition of participants was assessed four times within 12 months (t0: baseline, t1: 3 months, t2: 6 months, and t3: 12 months) by validated PROMs. We performed competing-risks regression based on Fine and Gray’s proportional sub-distribution hazards model for exploring factors associated with time-to-dropout. Death was considered as competing risk. ResultsThree hundred sixty-two participants were analyzed in the study. 193 (53.3%) completed follow-up at 12 months, 67 (18.5%) patients dropped out, and 102 patients (28.2%) died during the study period. Poor subjective social support was related to higher risk for drop-out (SHR=2.10; 95%CI: 1.01 – 4.35). Lower values in health-related quality of life were related to drop-out and death. The subscales global health status/QoL, role functioning, physical functioning, and fatigue symptom in the EORTC QLQ-C30 were key characteristics associated with early drop-out.ConclusionSeverely affected cancer patients with poor social support and poor quality of life seem more likely to drop out of studies compared to patients with higher levels of social support and quality of life. This should be considered when planning studies assessing cancer patients. Methods to monitor drop-outs timely and handle missing outcomes might be used. Results of such studies have to be interpreted with caution in light of the particular drop-out mechanisms.


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