Rogak, Lauren J

Background/Objectives: The PRO-CTCAE Average Composite Score (ACS), calculated as the mean of PRO-CTCAE composite scores, summarizes overall symptom and side effect burden. This study evaluated the test–retest reliability, responsiveness to change, known-groups validity, and sensitivity to group differences in the ACS. Methods: Analyses used the original PRO-CTCAE validation dataset, including lung (n = 174), breast (n = 222), and head and neck (n = 139) cancer cohorts, and data from the COMET-2 randomized phase III trial comparing cabozantinib (n = 53) and mitoxantrone–prednisone (n = 54) in men with previously treated prostate cancer. Test–retest reliability was assessed using intraclass correlation coefficients (ICCs) from two-way mixed-effects models for agreement. Responsiveness was evaluated by relating ACS change scores (Visit 1 minus follow-up Visit 2) to patient-reported global ratings of change (GRC; worsened, unchanged, or improved) using standardized response means (SRMs) and Jonckheere–Terpstra trend tests. Known-groups validity was examined by comparing mean ACS values between ECOG performance status groups (0–1 vs. 2–4). Sensitivity to treatment group differences was assessed using model-based area-under-the-curve (AUC) comparisons of longitudinal ACS trajectories. Results: Test–retest reliability was acceptable, with ICCs among GRC-defined stable patients of 0.80 (95% CI: 0.70–0.87) in lung cancer, 0.84 (95% CI: 0.77–0.89) in breast cancer, and 0.77 (95% CI: 0.63–0.86) in head and neck cancer; ICCs based on assessments completed one day apart ranged from 0.88 to 0.90. The ACS demonstrated responsiveness, with SRMs of 0.30/0.15/−0.37 (lung), 0.29/0.14/−0.40 (breast), and −0.01/−0.20/−0.56 (head/neck) for improved/no-change/worsened groups, respectively, and significant monotonic trends across GRC categories (all p < 0.01). Known-groups validity was supported by conceptually expected differences in ACS values across distinct levels of self-reported patient-reported physical functioning and ECOG performance status categories. Mean ACS values were lower among patients with good versus limited physical functioning (0.71 vs. 1.23 in lung cancer, 0.52 vs. 1.19 in breast cancer, and 0.69 vs. 1.29 in head and neck cancer) and among patients with ECOG PS 0–1 versus 2–4 (0.93 vs. 1.31, 0.74 vs. 1.22, and 0.90 vs. 1.06, respectively). In COMET-2, higher symptom burden was detected in the cabozantinib arm compared with the mitoxantrone–prednisone arm (AUC difference = 1.5, 95% CI: 0.2–2.8, p = 0.02). Conclusions: The ACS demonstrated acceptable test–retest reliability, responsiveness, and known-groups validity across multiple cancer populations. These findings support its use as a complementary summary measure of overall symptomatic adverse event burden alongside individual symptom-level analyses.

PURPOSE Remote symptom monitoring using patient-reported outcomes (PROs) has been shown to improve symptom control and physical function among patients with advanced cancer. However, it is unclear whether these benefits are similar across demographic groups. This exploratory analysis of the PRO-TECT trial examined whether the effects of electronic symptom monitoring varied by race, age, sex, and educational attainment. METHODS PRO-TECT was a cluster randomized trial conducted across 52 US community oncology practices comparing weekly electronic symptom monitoring with usual care (UC). Adult patients with metastatic solid tumors receiving systemic therapy were enrolled (N = 1,191). Participants in the PRO arm completed weekly symptom surveys including the PRO-CTCAE, triggering alerts to the care team for severe or worsening symptoms. Patients chose whether to complete weekly PROs online or via telephone-based interactive voice response not requiring Internet access. Outcomes were measured using the European Organisation for Research and Treatment of Cancer QLQ-C30 symptom control and physical function scales. Subgroup analyses were performed by race (Black v White), age (<65 v ≥65 years), sex (male v female), and educational attainment (≤high school v >high school). RESULTS From baseline to 3 months, PRO participants showed greater improvements in symptom control (+2.37 v −0.20, P = .002) and physical function (+1.54 v −0.93, P = .02) versus UC. Benefits were most pronounced among younger, female, Black, and less educated participants. Black participants in the PRO arm were more likely to report that symptom reporting made them feel more in control of their care compared with White participants. CONCLUSION Electronic symptom monitoring improved quality-of-life outcomes overall, including among groups who have historically experienced higher symptom burden or barriers to communication. Remote PRO systems may represent an equitable strategy to enhance cancer care delivery.

Background: The PRO-CTCAE provides patient-reported data on symptomatic AEs. A summary metric—the ACS—reflecting total AE burden can be calculated by averaging AE-level composite scores at a given timepoint for each participant. This study investigated the psychometric properties and interpretability of this PRO-CTCAE ACS in patients with breast, lung, or head/neck cancers. Methods: We conducted a secondary analysis of a PRO-CTCAE validation dataset comprising 940 adults undergoing chemotherapy or radiation therapy (clinicaltrials.gov: NCT02158637). We focused on empirically recommended symptom terms for three cancer sites. Analyses included Spearman’s correlations, coefficient alpha, and eigenvalues from the correlation matrices, confirmatory factor analysis (CFA), and principal component analysis (PCA). Latent profile analysis (LPA) was used to assess ACS interpretability in the lung cohort. Results: Mean composite score inter-correlations were moderate (0.30–0.35), and coefficient alphas were high (0.81–0.91). Eigenvalue ratios and CFA supported retention of a single factor/component, with suitable model fit indices. ACS correlated highly with factor scores and the first principal component from the PCA. Reduced sets of terms produced reliable scores that closely approximated the full set scores and aligned with external criteria. LPA in the lung subgroup identified four latent classes; ACS differentiated high vs. low symptom burden groups but did not distinguish the two groups expressing distinct symptom profiles. Conclusion: The ACS demonstrated structural validity through adequately fitting linear factor models and effectively summarized symptomatic AE burden. However, similar ACS values may mask clinically distinct symptomatic AE profiles, underscoring the value of both summary metrics and profile-based approaches.

PURPOSE Patients with cancer take different types of medications with varying schedules and settings. They are also sometimes instructed to stop medications due to toxicity. To measure self-reported nonadherence in this heterogeneous population, we modified and evaluated a measure originally developed to assess nonadherence to daily oral antihypertensives, the Domains of Subjective Extent of Nonadherence (DOSE-Nonadherence). METHODS The measure was refined in an iterative process incorporating feedback from patient investigators and participant interviews in English and Spanish. Branching logic was added for participant selection of medication administration setting: (1) only home, (2) only clinic, or (3) partly home/partly clinic. Participants reported their adherence to medications taken over a setting-specific reference period (1 week for home, 1 month for clinic medications). Participants who missed medications then reported on reasons for nonadherence. Adherence was dichotomized for analysis (complete adherence v any nonadherence). For participants who received clinic-administered medications, concordance between chart-abstracted and self-reported adherence was evaluated. RESULTS Seventy-three participants completed the measure (68% English; 32% Spanish; 86% female; 44% age ≥60 years). The majority had breast cancer; 64% had metastatic disease. Twenty-six percent (15/58) of participants who received medication in clinic and 24% (11/46) of those who took medication at home reported nonadherence. Participants felt able to respond accurately to both reference periods and perceived all reasons for nonadherence to be relevant. Among participants who completed the final version of the measure for clinic-administered medication, 96% (26/27) accurately reported their adherence compared with chart-abstracted data. CONCLUSION Our results support the validity of the DOSE-Nonadherence-Cancer for assessing cancer treatment nonadherence. This measure can be used to assess nonadherence in patients with cancer receiving a broad array of systemic therapies.

Background/Aims: The Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE ® ) was developed to capture symptomatic adverse events from the patient perspective. We aim to describe statistical properties of PRO-CTCAE items and summary scores and to provide evidence for recommendations regarding PRO-CTCAE administration and reporting. Methods: Using data from the PRO-CTCAE validation study (NCT02158637), prevalence, means, and standard deviations of PRO-CTCAE items, composite scores, and mean and maximum scores across attributes (frequency, severity, and/or interference) of symptomatic adverse events were calculated. For each adverse event, correlations and agreement between attributes, correlations between attributes and composite scores, and correlations between composite, mean, and maximum scores were estimated. Results: PRO-CTCAE items were completed by 899 patients with various cancer types. Most patients reported experiencing one or more adverse events, with the most prevalent being fatigue (87.7%), sad/unhappy feelings (66.0%), anxiety (63.6%), pain (63.2%), insomnia (61.8%), and dry mouth (60.0%). Attributes were moderately to strongly correlated within an adverse event ( r = 0.53 to 0.77, all p < 0.001) but not fully concordant (κ weighted = 0.26 to 0.60, all p < 0.001), with interference demonstrating lowest mean scores and prevalence among attributes of the same adverse event. Attributes were moderately to strongly correlated with composite scores ( r = 0.67 to 0.97, all p < 0.001). Composite scores were moderately to strongly correlated with mean and maximum scores for the same adverse event ( r = 0.69 to 0.94, all p < 0.001). Correlations between composite scores of different adverse events varied widely ( r = 0.04 to 0.68) but were moderate to strong for conceptually related adverse events. Conclusions: Results provide evidence for PRO-CTCAE administration and reporting recommendations that the full complement of attributes be administered for each adverse event, and that attributes as well as summary scores be reported.