Real time patient-reported outcome measures in patients with cancer: Early experience within an integrated health system.

BACKGROUND: While patient-reported outcome measures (PROMs) have benefit in cancer clinical trials, real-world applications are lacking. This study describes the method of implementation of a cancer enterprise-wide PROMs platform. METHODS: After establishing a multispecialty stakeholder group within a large integrated health system, domain-specific instruments were selected from the National Institutes of Health's Patient-Reported Outcomes Measurement Information System (PROMIS) instruments (pain interference, fatigue, physical function, and depression) and were administered at varying frequencies throughout each patient's cancer journey. All cancer patients with an oncologic visit were eligible to complete the PROMs prior to the visit using a patient portal, or at the time of the visit using a tablet. PROMs were integrated into clinical workflow. Clinical partnerships were essential for successful implementation. Descriptive preliminary data were compared using multivariable logistic regression to determine the factors associated with method of PROMs completion. RESULTS: From September 16, 2020 to July 23, 2021, 23 of 38 clinical units (60.5%) implemented PROMs over 2392 encounters and 1666 patients. Approximately one third of patients (n = 629, 37.8%) used the patient portal. Black patients (aOR 0.70; 95% CI: 0.51-0.97) and patients residing in zip codes with higher percentage of unemployment (aOR: 0.07, 95% CI: 0.01-0.41) were among the least likely to complete PROMs using the patient portal. CONCLUSIONS: Successful system-wide implementation of PROMs among cancer patients requires engagement from multispecialty stakeholders and investment from clinical partners. Attention to the method of PROMs collection is required in order to reduce the potential for disparities, such as Black populations and those residing in areas with high levels of unemployment.

Adherence with National Comprehensive Cancer Network posttreatment surveillance guidelines in patients with head and neck cancer.

BACKGROUND: Surveillance in head and neck cancer (HNC) is essential to detect recurrent or new lesions and to optimize function. This study describes drivers of surveillance adherence in patients with HNC and its effect on prognosis. METHODS: Adherence with surveillance of HNC patients was determined using the National Comprehensive Cancer Network HNC guidelines. Logistic regression and Cox proportional hazards models were used to determine predictors of adherence and overall survival (OS). RESULTS: Results showed that 110 of 221 patients (50.2%) were adherent with surveillance. Distance from the treatment center was the only significant association. Adherence was not associated with OS following multivariate adjustment (adjusted hazard ratio [aHR] = 0.68, 95% confidence interval [CI] = 0.43-1.09). However, 5-10 years after treatment completion, adherence was an independent predictor of survival (aHR = 0.24, 95% CI = 0.09-0.61). CONCLUSION: Adherence with surveillance is important in improving survival in patients with HNC, especially in the long term.

Effect of Tumor Size and Minimal Extrathyroidal Extension in Patients with Differentiated Thyroid Cancer.

INTRODUCTION: Risk-stratified treatment strategies have become a focus in the treatment of differentiated thyroid cancer (DTC). In the 2015 American Thyroid Association treatment guidelines, adjuvant treatment with radioactive iodine (RAI) is considered in the presence of minimal extrathyroidal extension (mETE). This study aimed to investigate the prognostic significance of mETE and tumor size in patients with DTC. METHODS: A retrospective review was undertaken of 2323 consecutive patients treated surgically for T1-T3 (defined per seventh edition of the American Joint Committee on Cancer staging criteria) and M0 DTC from 2000 to 2015 at The University of Texas MD Anderson Cancer Center. Patients were divided into four groups according to the size of the tumor (≤4 cm vs. >4 cm) and the presence of mETE. Predictors of disease-free survival (DFS), disease-specific survival, locoregional failure (LRF), and distant metastatic failure (DMF) were compared using the log-rank test and Cox's proportional hazards models. RESULTS: There were only seven DTC-related deaths, limiting the clinical significance of the analysis, especially of overall and disease-specific survival. Following multivariate analysis, patients with tumors >4 cm did worse than patients with tumors ≤4 cm with respect to DFS (group 3 [>4 cm without mETE] adjusted hazard ratio (HRadj) = 2.1 [confidence interval (CI) 1.1-3.8]; group 4 [>4 cm with mETE] HRadj = 2.9 [CI 1.6-5.1]). However, patients did not differ according to DFS, regardless of the presence of mETE within each size category (group 2 [≤4 cm with mETE] vs. group 1 [≤4 cm without mETE] HRadj = 1.3 [CI 0.9-1.8]; group 4 [>4 cm without mETE] vs. group 3 [>4 cm with mETE] HRadj = 1.0 [CI 0.5-2.3]). For LRF and DMF, size but not mETE was also an independent risk factor. CONCLUSION: Tumor size, but not the presence of mETE, was an independent predictor of DFS, LRF, and DMF in DTC.