Symptom Assessment in Relapsed Small Cell Lung Cancer: Cross-Validation of the Patient Symptom Assessment in Lung Cancer Instrument

IntroductionLung cancer symptoms can be burdensome for patients with small cell lung cancer (SCLC). Patient Symptom Assessment in Lung Cancer (PSALC), a self-report scale for assessing SCLC symptom burden, was developed and validated previously using intravenous topotecan clinical trial data. This study cross-validates the PSALC using oral topotecan (OT) trial data.MethodsData were analyzed from a randomized, open-label, multicenter trial including 71 patients with relapsed SCLC receiving OT with best supportive care and 70 patients receiving best supportive care alone. PSALC and EQ-5D were administered at baseline and at 3-week intervals. Internal consistency, reliability, construct validity, and responsiveness were evaluated.ResultsOnly one factor was indicated in factor analysis, hence PSALC total score (PSALC-TS) was used for psychometric analysis. Internal consistency was supported by Cronbach's alpha of 0.78. Construct validity was supported by significant associations of higher PSALC-TS (higher symptom burden) with worse Eastern Cooperative Oncology Group performance status and by correlations of PSALC-TS with EQ-5D utility index and visual analog scale score (all p < 0.001). Reliability was supported by intraclass correlation coefficient of 0.68 (using PSALC-TS before clinical status change) and concordance correlation coefficient of 0.69 (using PSALC-TS at baseline and before first visit). PSALC-TS was responsive to clinical status change from baseline to tumor response (responsiveness statistic = −0.99) and to tumor progression (responsiveness statistic = 0.94).ConclusionsConsistent with prior psychometric results, this cross-validation study using OT trial data showed acceptable validity, reliability, and responsiveness of the PSALC scale, further supporting its use to measure symptom burden in previously treated SCLC

Impact of atypical long-acting injectable versus oral antipsychotics on rehospitalization rates and emergency room visits among relapsed schizophrenia patients: a retrospective database analysis

BACKGROUND: Among schizophrenia patients relapsed on an oral antipsychotic (AP), this study compared the impact of switching to atypical AP long-acting injectable therapy (LAT) versus continuing oral APs on hospitalization and emergency room (ER) visit recurrence. METHODS: Electronic records from the Premier Hospital Database (2006-2010) were analyzed. Adult patients receiving oral APs during a schizophrenia-related hospitalization were identified and, upon relapse (i.e., rehospitalization for schizophrenia), were stratified into (a) patients switching to atypical LAT and (b) patients continuing with oral APs. Atypical LAT relapse patients were matched 1:3 with oral AP relapse patients, using a propensity score model. Andersen-Gill Cox proportional hazards models assessed the impact of atypical LAT versus oral AP on time to multiple recurrences of all-cause hospitalizations and ER visits. No adjustment was made for multiplicity. RESULTS: Atypical LAT (N = 1032) and oral AP (N = 2796) patients were matched and well-balanced with respect to demographic (mean age: 42.1 vs 42.4 years, p = .5622; gender: 43.6% vs 44.6% female, p = .5345), clinical, and hospital characteristics. Over a mean 30-month follow-up period, atypical LATs were associated with significantly lower mean number of rehospitalizations (1.25 vs 1.61, p < .0001) and ER visits (2.33 vs 2.67, p = .0158) compared with oral APs, as well as fewer days in hospital (mean days: 13.46 vs. 15.69, p = .0081). Rehospitalization (HR 0.81, 95% CI 0.76–0.87, p < .0001) and ER visit (HR 0.88, 95% CI 0.87–0.93, p < .0001) rates were significantly lower for patients receiving atypical LAT versus oral APs. CONCLUSIONS: This hospital database analysis found that in relapsed schizophrenia patients, atypical LATs were associated with lower rehospitalization and ER visit rates than oral APs

Safety and treatment patterns of multikinase inhibitors in patients with metastatic renal cell carcinoma at a tertiary oncology center in Italy

<p>Abstract</p> <p>Background</p> <p>Multikinase inhibitors (MKIs) sunitinib and sorafenib have become a standard of care for metastatic renal cell carcinoma (mRCC). This study assessed safety and treatment patterns for these agents in a real-world clinical practice setting in Italy.</p> <p>Methods</p> <p>A retrospective medical record review was performed at a tertiary oncology center in Italy. The study included MKI-naïve non-trial patients ≥18 years old, with a histological diagnosis of mRCC, and who received sunitinib or sorafenib as first MKI during 9/2005-7/2008. Data were collected on adverse events (AEs), treatment modifications (discontinuations, interruptions, dose changes), and reasons for these modifications.</p> <p>Results</p> <p>145 patients were included; 85 received sunitinib and 60 received sorafenib as first-line MKI. Median treatment duration was 6.6 (sunitinib) and 5.8 (sorafenib) months. 97.6% and 70.0% of patients receiving sunitinib and sorafenib, respectively, experienced ≥1 AE; 27.1% and 31.7% had ≥1 grade 3/4 AE. The most common any grade AE for sunitinib was fatigue/asthenia (81.2%), followed by mucositis/stomatitis (58.8%) and decreased taste sensation (42.4%), while for sorafenib this was fatigue/asthenia (43.3%) followed by hand-foot syndrome (38.3%) and diarrhea (31.7%). Treatment discontinuation, interruption, and dose reduction due to AEs occurred in 11.8%, 23.5%, and 30.6%, respectively, of patients receiving sunitinib, and 5.0%, 23.3%, and 36.7%, respectively, of patients receiving sorafenib.</p> <p>Conclusions</p> <p>In this retrospective study, most patients experienced ≥1 AE during first-line MKI treatment. AEs were reported frequently and resulted in treatment modifications in 40% of patients receiving sunitinib and 45% of patients receiving sorafenib. These results suggest a need for additional effective and more tolerable treatments for mRCC.</p

Digital health technologies and machine learning augment patient reported outcomes to remotely characterise rheumatoid arthritis

Digital measures of health status captured during daily life could greatly augment current in-clinic assessments for rheumatoid arthritis (RA), to enable better assessment of disease progression and impact. This work presents results from weaRAble-PRO, a 14-day observational study, which aimed to investigate how digital health technologies (DHT), such as smartphones and wearables, could augment patient reported outcomes (PRO) to determine RA status and severity in a study of 30 moderate-to-severe RA patients, compared to 30 matched healthy controls (HC). Sensor-based measures of health status, mobility, dexterity, fatigue, and other RA specific symptoms were extracted from daily iPhone guided tests (GT), as well as actigraphy and heart rate sensor data, which was passively recorded from patients’ Apple smartwatch continuously over the study duration. We subsequently developed a machine learning (ML) framework to distinguish RA status and to estimate RA severity. It was found that daily wearable sensor-outcomes robustly distinguished RA from HC participants (F1, 0.807). Furthermore, by day 7 of the study (half-way), a sufficient volume of data had been collected to reliably capture the characteristics of RA participants. In addition, we observed that the detection of RA severity levels could be improved by augmenting standard patient reported outcomes with sensor-based features (F1, 0.833) in comparison to using PRO assessments alone (F1, 0.759), and that the combination of modalities could reliability measure continuous RA severity, as determined by the clinician-assessed RAPID-3 score at baseline (r2, 0.692; RMSE, 1.33). The ability to measure the impact of disease during daily life—through objective and remote digital outcomes—paves the way forward to enable the development of more patient-centric and personalised measurements for use in RA clinical trials

Digital health technologies and machine learning augment patient reported outcomes to remotely characterise rheumatoid arthritis

Digital measures of health status captured during daily life could greatly augment current in-clinic assessments for rheumatoid arthritis (RA), to enable better assessment of disease progression and impact. This work presents results from weaRAble-PRO, a 14-day observational study, which aimed to investigate how digital health technologies (DHT), such as smartphones and wearables, could augment patient reported outcomes (PRO) to determine RA status and severity in a study of 30 moderate-to-severe RA patients, compared to 30 matched healthy controls (HC). Sensor-based measures of health status, mobility, dexterity, fatigue, and other RA specific symptoms were extracted from daily iPhone guided tests (GT), as well as actigraphy and heart rate sensor data, which was passively recorded from patients’ Apple smartwatch continuously over the study duration. We subsequently developed a machine learning (ML) framework to distinguish RA status and to estimate RA severity. It was found that daily wearable sensor-outcomes robustly distinguished RA from HC participants (F1, 0.807). Furthermore, by day 7 of the study (half-way), a sufficient volume of data had been collected to reliably capture the characteristics of RA participants. In addition, we observed that the detection of RA severity levels could be improved by augmenting standard patient reported outcomes with sensor-based features (F1, 0.833) in comparison to using PRO assessments alone (F1, 0.759), and that the combination of modalities could reliability measure continuous RA severity, as determined by the clinician-assessed RAPID-3 score at baseline (r2, 0.692; RMSE, 1.33). The ability to measure the impact of the disease during daily life—through objective and remote digital outcomes—paves the way forward to enable the development of more patient-centric and personalised measurements for use in RA clinical trials

Renal toxicity in patients with multiple myeloma receiving zoledronic acid vs. ibandronate: A retrospective medical records review

Aims : This retrospective study investigated the rates of renal impairment in patients with multiple myeloma treated with zoledronic acid and ibandronate. Materials and Methods : We retrospectively reviewed medical records in a German oncology clinic, from May 2001 to December 2005. Creatinine measurements were analyzed from baseline (before zoledronic acid or ibandronate treatment) to last evaluation for each patient. A total of 84 patients were included. Results : Zoledronic acid increased the risk of renal impairment by approximately 3-fold compared with ibandronate (renal impairment rates: zoledronic acid 37.7% vs. ibandronate 10.5%, relative risk [RR]=3.6, P=0.0029 serum creatinine [SCr]; 62.3% vs. 23.7%, RR=2.6, P=0.0001 glomerular filtration rate [GFR]). Ibandronate-treated patients switched from zoledronic acid had a significantly higher risk of renal impairment than patients receiving ibandronate monotherapy (zoledronic acid over ibandronate 39.1% vs. ibandronate monotherapy 6.7%, RR= 5.9, P=0.028 [SCr]; 65.2% vs 26.7%, RR=2.4, P=0.022 [GFR]). Multivariate analysis found significantly higher hazard ratios for zoledronic acid over ibandronate (SCr: Cox = 4.38, P=0.01; Andersen-Gill=8.22, P &lt; 0.01; GFR: Cox = 4.31, P &lt; 0.01; Andersen-Gill = 3.71, P &lt; 0.01). Conclusions : Overall, this retrospective study suggests that multiple myeloma patients are more likely to experience renal impairment with zoledronic acid than with ibandronate. The risk of renal impairment increased if patients had received prior therapy with zoledronic acid

Identifying Motor, Emotional-Behavioral, and Cognitive Deficits that Comprise the Triad of HD Symptoms from Patient, Caregiver, and Provider Perspectives

Background: The objective of this study was to identify important attributes associated with the triad of symptoms (cognition, emotional–behavioral, and motor) of Huntington's disease (HD) from patient, caregiver, and medical provider perspectives to facilitate development of a new disease‐specific, health‐related quality of life (HRQOL) instrument. Methods: We conducted a targeted literature review of HD and HRQOL instruments, expert surveys, and patient and caregiver phone‐based interviews to extract information on the symptoms and issues most relevant to the HD symptom triad (HD triad). The data collected from these sources were used to generate themes and subdomains and to develop an integrated schema that highlights the key dimensions of the triad. Results: The search identified the following areas: emotional functioning/behavioral changes (e.g., positive emotions, sadness/depression); cognitive functioning (e.g., memory/learning, attention/comprehension); physical functioning (e.g., motor functioning, medication); social functioning (e.g., leisure, interpersonal relationships); end‐of‐life concerns/planning; and gene testing. Fifteen individuals diagnosed with HD and 16 HD caregivers, recruited from several Huntington's Disease Society of America support group networks, completed phone interviews. Nineteen US medical providers who specialize in HD completed the online survey. Twenty‐six subdomains of the HD symptom triad (seven cognition, 12 emotional–behavioral, and seven motor) emerged relatively consistently across patient, caregiver, and provider samples. These included movements/chorea, memory impairment, depression, and anxiety. Discussion: Based on an integrated, mixed‐methods approach, important HD triad symptom were identified and organized into a guiding schema. These patient‐, caregiver‐, and provider‐triangulated data served as the basis for development of a HD‐specific HRQOL instrument, the HD‐PRO‐TRIAD™