Expanding patient-reported outcomes to oral health complications from systemic cancer therapy.

2012 ◽  
Vol 30 (34_suppl) ◽  
pp. 60-60
Author(s):  
Rebecca A. Miksad ◽  
Rohit Goyal ◽  
G. Scott Gazelle ◽  
J. Shannon Swan
Keyword(s):  
Oral Health ◽  
Side Effects ◽  
Cancer Therapy ◽  
Performance Measurement ◽  
Cancer Patients ◽  
Patient Reported Outcomes ◽  
Full Range ◽  
Cross Sectional ◽  
Patient Reported ◽  
Health Complications

60 Background: Cross-disciplinary patient reported outcomes (PROs) assess the full range of side effects from systemic cancer therapy. For oral health complications, however, the validity of oral-health specific and generic health-related quality-of-life (QoL) instruments is unknown for cancer patients. This study evaluates the performance, measurement, and prediction characteristics of the Oral Health Impact Profile (OHIP–14) and EQ–5D in cancer patients with bisphosphonate-associated Osteonecrosis of the Jaw (ONJ). Methods: 34 cancer patients assessed the QoL of their own ONJ with the OHIP–14 and evaluated the QoL of 4 standardized ONJ Health States with the EQ–5D, as previously published. For each instrument, the standard response mean (SRM), effect size (ES), and ability to distinguish minimally important differences (MID) were evaluated for ONJ compared to baseline (longitudinal responsiveness). Instrument MIDs (cross-sectional responsiveness) were also calculated. Performance of a published general dentistry algorithm to predict EQ–5D values from OHIP–14 results was tested. Results: The OHIP–14 and EQ-5D instruments demonstrated moderate to large longitudinal and cross-sectional responsiveness. Pain was one of the most responsive domains for both instruments. Ceiling/floor effects were most prominent for OHIP–14. A general dentistry algorithm did not adequately predict EQ–5D values for cancer patients. Conclusions: This study provides the first empirical evidence for the performance, measurement, and prediction characteristics of oral-health specific and generic QoL instruments for the oral health side effects of systemic cancer treatment. Instrument validity is supported for oral health complications in cancer patients. These results provide benchmarks for PROs at the intersection of oral medicine and surgery, dentistry, and oncology. [Table: see text]

scholarly journals A Factor Analysis Approach for Clustering Patient Reported Outcomes

2016 ◽  
Vol 55 (05) ◽  
pp. 431-439 ◽  
Author(s):  
Maria Thor ◽  
Caroline Olsson ◽  
Viktor Skokic ◽  
Rebecka Jörnsten ◽  
David Alsadius ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Quantitative Analysis ◽  
Side Effects ◽  
Radiation Dose ◽  
Cancer Patients ◽  
Patient Reported Outcomes ◽  
Dose Volume ◽  
Patient Reported ◽  
Symptom Group ◽  
The Relationship

SummaryBackground: In the field of radiation oncology, the use of extensive patient reported outcomes is increasingly common to meas -ure adverse side effects after radiotherapy in cancer patients. Factor analysis has the potential to identify an optimal number of latent factors (i.e., symptom groups). However, the ultimate goal of treatment response modeling is to understand the relationship between treatment variables such as radiation dose and symptom groups resulting from FA. Hence, it is crucial to identify clinically more relevant symptom groups and improved response variables from those symptom groups for a quantitative analysis. Objectives: The goal of this study is to design a computational method for finding clinically relevant symptom groups from PROs and to test associations between symptom groups and radiation dose. Methods: We propose a novel approach where exploratory factor analysis is followed by confirmatory factor analysis to determine the relevant number of symptom groups. We also propose to use a combination of symptoms in a symptom group identified as a new response variable in linear regression analysis to investigate the relationship between the symptom group and dose-volume variables. Results: We analyzed patient-reported gastrointestinal symptom profiles from 3 datasets in prostate cancer patients treated with radiotherapy. The final structural model of each dataset was validated using the other two datasets and compared to four other existing FA methods. Our systematic EFA-CFA approach provided clinically more relevant solutions than other methods, resulting in new clinically relevant outcome variables that enabled a quantitative analysis. As a result, statistically significant correlations were found between some dose- volume variables to relevant anatomic structures and symptom groups identified by FA. Conclusions: Our proposed method can aid in the process of understanding PROs and provide a basis for improving our understanding of radiation-induced side effects.

scholarly journals Full, partial and modified permutations of the Mayo Score: Characterizing clinical and patient-reported outcomes in ulcerative colitis patients

2021 ◽  
Author(s):  
April N Naegeli ◽  
Theresa Hunter ◽  
Yan Dong ◽  
Ben Hoskin ◽  
Chloe Middleton-Dalby ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Patient Reported Outcomes ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Assessment Scores ◽  
Mayo Score ◽  
Patient Reported ◽  
Practice Trials ◽  
Highly Correlated

Abstract Background Understanding ulcerative colitis (UC) disease activity assessed via the full, modified or partial Mayo Score may help clinicians apply results from clinical trials to practice and facilitate interpretation of recent and older studies. Methods Mayo Score variables were assessed in a cross-sectional study of 2608 UC patients. Results Permutations of Mayo Scores were highly correlated, and models predicting the omitted variable from each permutation demonstrated significant agreement between predicted and observed values. Conclusions Partial/modified Mayo Scores may be used to predict endoscopic and Physician's Global Assessment scores, and serve as proxies for the full Mayo Score in clinical practice/trials.

scholarly journals Electronic patient-reported outcomes and machine learning in predicting immune-related adverse events of immune checkpoint inhibitor therapies

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sanna Iivanainen ◽  
Jussi Ekstrom ◽  
Henri Virtanen ◽  
Vesa V. Kataja ◽  
Jussi P. Koivunen
Keyword(s):  
Machine Learning ◽  
Early Detection ◽  
Adverse Events ◽  
Cancer Patients ◽  
Immune Checkpoint ◽  
Patient Reported Outcomes ◽  
Prediction Models ◽  
Accuracy Score ◽  
Patient Reported ◽  
Auc Value

Abstract Background Immune-checkpoint inhibitors (ICIs) have introduced novel immune-related adverse events (irAEs), arising from various organ systems without strong timely dependency on therapy dosing. Early detection of irAEs could result in improved toxicity profile and quality of life. Symptom data collected by electronic (e) patient-reported outcomes (PRO) could be used as an input for machine learning (ML) based prediction models for the early detection of irAEs. Methods The utilized dataset consisted of two data sources. The first dataset consisted of 820 completed symptom questionnaires from 34 ICI treated advanced cancer patients, including 18 monitored symptoms collected using the Kaiku Health digital platform. The second dataset included prospectively collected irAE data, Common Terminology Criteria for Adverse Events (CTCAE) class, and the severity of 26 irAEs. The ML models were built using extreme gradient boosting algorithms. The first model was trained to detect the presence and the second the onset of irAEs. Results The model trained to predict the presence of irAEs had an excellent performance based on four metrics: accuracy score 0.97, Area Under the Curve (AUC) value 0.99, F1-score 0.94 and Matthew’s correlation coefficient (MCC) 0.92. The prediction of the irAE onset was more difficult with accuracy score 0.96, AUC value 0.93, F1-score 0.66 and MCC 0.64 but the model performance was still at a good level. Conclusion The current study suggests that ML based prediction models, using ePRO data as an input, can predict the presence and onset of irAEs with a high accuracy, indicating that ePRO follow-up with ML algorithms could facilitate the detection of irAEs in ICI-treated cancer patients. The results should be validated with a larger dataset. Trial registration Clinical Trials Register (NCT3928938), registration date the 26th of April, 2019

Objective and Subjective Outcomes in Patients with Hearing Aids: A Cross-Sectional, Comparative, Associational Study

2021 ◽  
pp. 1-9
Author(s):  
Xunyi Wang ◽  
Yun Zheng ◽  
Gang Li ◽  
Jingzhe Lu ◽  
Yan Yin
Keyword(s):  
Hearing Aids ◽  
Patient Reported Outcomes ◽  
Cross Sectional ◽  
Patient Reported ◽  
Objective Tests ◽  
The Difference ◽  
Potential Factors ◽  
Positive Correlations ◽  
The Relationship ◽  
Subjective Outcomes

<b><i>Introduction:</i></b> Outcome assessment for hearing aids (HAs) is an essential part of HA fitting and validation. There is no consensus about the best or standard approach for evaluating HA outcomes. And, the relationship between objective and subjective measures is ambiguous. This study aimed to determine the outcomes after HA fitting, explore correlations between subjective benefit and acoustic gain improvement as well as objective audiologic tests, and investigate several variables that may improve patients’ perceived benefits. <b><i>Methods:</i></b> Eighty adults with bilateral symmetrical hearing loss using HAs for at least 1 month were included in this study. All subjects completed the pure tone average (PTA) threshold and word recognition score (WRS) tests in unaided and aided conditions. We also administered the Chinese version of International Outcome Inventory for Hearing Aids (IOI-HA), to measure participants’ subjective benefits. Objective HA benefit (acoustic gain improvement) was defined as the difference in thresholds or scores between aided and unaided conditions indicated with ΔPTA and ΔWRS. Thus, patients’ baseline hearing levels were taken into account. Correlations were assessed among objective audiologic tests (PTA and WRS), acoustic gain improvement (ΔPTA and ΔWRS), multiple potential factors, and IOI-HA overall scores. <b><i>Results:</i></b> PTA decreased significantly, but WRS did not increase when aided listening was compared to unaided listening. Negative correlations between PTAs and IOI-HA scores were significant but weak (<i>r</i> = −0.370 and <i>r</i> = −0.393, all <i>p</i> &#x3c; 0.05). Significant weak positive correlations were found between WRSs and IOI-HA (<i>r</i> = 0.386 and <i>r</i> = 0.309, all <i>p</i> &#x3c; 0.05). However, there was no correlation among ΔPTA, ΔWRS, and IOI-HA (<i>r</i> = 0.056 and <i>r</i> = −0.086, all <i>p</i> &#x3e; 0.05). Moreover, 2 nonaudiological factors (age and daily use time) were significantly correlated with IOI-HA (<i>r</i> = −0.269 and <i>r</i> = 0.242, all <i>p</i> &#x3c; 0.05). <b><i>Conclusions:</i></b> Correlations among objective audiologic tests, acoustic gain, and subjective patient-reported outcomes were weak or absent. Subjective questionnaires and objective tests do not reflect the same hearing capability. Therefore, it is advisable to evaluate both objective and subjective outcomes when analyzing HA benefits on a regular basis and pay equal attention to nonaudiological and audiological factors.

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