ImportanceAcute promyelocytic leukemia (APL) is an acute illness that presents with cytopenia, infections, and disseminated intravascular coagulation. Achieving remission has been shown to make a major difference in patient outcomes; however, early death rates in the first month have been as high as 30% due to acute presentation, comorbidities, the rarity of APL, and clinician inexperience.ObjectiveTo develop treatment strategies that would decrease estimated 1-month mortality from 30% to below 15%.Design, Setting, and ParticipantsIn this nonrandomized clinical trial, a treatment algorithm that focused on supportive care was used to prevent early death in patients with APL treated at academic and community health centers between August 2017 and July 2021. Because of the rarity of the disease, expert support was available 24/7 from 7 designated APL experts at 6 participating academic lead centers, and included an additional 293 community centers. When a patient presented with APL, an expert was contacted and a consensus treatment plan was developed using the algorithm and expert suggestions. There were no exclusion criteria and all patients with a confirmed diagnosis of APL regardless of age or comorbid conditions were enrolled. Expert support was provided throughout induction. Initial data analysis was conducted May 2023.Main Outcomes and MeasuresOne-month mortality; additional objectives were to compare outcomes in academic and community centers and assess 1-year and overall survival.ResultsA total of 201 patients were enrolled from 43 centers; 62 at lead centers and 139 from 37 community centers. The median age was 53 years (range, 18-91 years), with 72 patients (35.8%) who were aged 60 years or older; 105 patients (52.2%) were male. Fifty-two patients (26.4%) were diagnosed with high-risk APL. The 1-month mortality rate was 6 deaths of 201 patients (3.0%; 95% CI, 1.1%-6.4%) after adjusting for 1 interim analysis. In a secondary analysis using the Kaplan-Meier method, the 1-month overall survival (OS) rate was 97.0% (95% CI, 93.5%-98.6%) and the 1-year OS rate was 94.5% (95% CI, 90.3%-96.9%).Conclusions and RelevanceIn this nonrandomized clinical trial, use of an algorithm combined with expert support resulted in a dramatic decrease in early death in academic and community centers. Population-wide survival improved in this highly curable disease, which suggests that implementing an accessible support system with APL experts for comanagement is the most logical next step.Trial RegistrationClinicalTrials.gov Identifier: NCT03253848
A Cohort Study to Evaluate Genetic Predictors of Aromatase Inhibitor Musculoskeletal Symptoms: Results from ECOG-ACRIN E1Z11
Abstract Purpose: Aromatase inhibitor (AI)–associated musculoskeletal symptoms (AIMSS) are common and frequently lead to AI discontinuation. SNPs in candidate genes have been associated with AIMSS and AI discontinuation. E1Z11 is a prospective cohort study designed to validate the association between 10 SNPs and AI discontinuation due to AIMSS. Patients and Methods: Postmenopausal women with stage I to III hormone receptor–positive breast cancer received anastrozole 1 mg daily and completed patient-reported outcome measures to assess AIMSS (Stanford Health Assessment Questionnaire) at baseline, 3, 6, 9, and 12 months. We estimated that 40% of participants would develop AIMSS and 25% would discontinue AI treatment within 12 months. Enrollment of 1,000 women with a fixed number per racial stratum provided 80% power to detect an effect size of 1.5 to 4. SNPs were found in ESR1 (rs2234693, rs2347868, and rs9340835), CYP19A1 (rs1062033 and rs4646), TCL1A (rs11849538, rs2369049, rs7158782, and rs7159713), and HTR2A (rs2296972). Results: Of the 970 evaluable women, 43% developed AIMSS and 12% discontinued AI therapy within 12 months. Although more Black and Asian women developed AIMSS than White women (49% vs. 39%, P = 0.017; 50% vs. 39%, P = 0.004, respectively), the AI discontinuation rates were similar across groups. None of the SNPs were significantly associated with AIMSS or AI discontinuation in the overall population or in distinct cohorts. The OR for rs2296972 (HTR2A) approached significance for developing AIMSS. Conclusions: We were unable to prospectively validate candidate SNPs previously associated with AI discontinuation due to AIMSS. Future analyses will explore additional genetic markers, patient-reported outcome predictors of AIMSS, and differences by race.
A Simplified Patient Care Strategy to Decrease Early Deaths in Acute Promyelocytic Leukemia (APL): Results of the ECOG-ACRIN EA9131 Trial
Predictive value of baseline patient-rated treatment bother for early anastrozole discontinuation in a racially diverse cohort: Results from ECOG-ACRIN E1Z11.
12094 Background: The Functional Assessment of Cancer Therapy patient-reported outcomes (PRO) item GP5 (“I am bothered by side effects of treatment”) estimates treatment tolerability. We aimed to extend our previous finding that GP5 predicts early aromatase inhibitor (AI) discontinuation (E1Z03, 96% White) in the racially diverse E1Z11 trial cohort. Methods: E1Z11 was coordinated by the ECOG-ACRIN NCI Community Oncology Research Program (NCORP) Research Base. Postmenopausal women initiating anastrozole per clinical care for ER+ stage I-III breast cancer with a pain score 0-3/10 and no rheumatologic comorbidities were eligible. Accrual of a racially diverse cohort of 1,000 women, including Black and Asian women, was planned. GP5 was administered prior to initiating anastrozole (trial baseline) and at 3, 6, 9 and 12 months. GP5 was scored on a 5-point Likert scale from 0 (not at all) to 4 (very much) and dichotomized as no/little treatment bother (0/1) or moderate/high treatment bother (2-4), consistent with previous analyses. A univariate Cox proportional hazards model estimated baseline GP5’s association with treatment duration via hazard ratio (HR). Early treatment discontinuation status was defined as treatment duration < 12 months with discontinuation not attributed to disease progression or death (n = 4), consistent with previous analyses. Results: 1,046 women enrolled from 6/2013-10/2018 (640 White, 201 Black, 205 Asian), including 590 (56%) from NCORP Community or Minority/Underserved Sites. Approximately 10% (100/987 with GP5 data) reported moderate/high treatment bother prior to initiating anastrozole. Anastrozole discontinuation rate at 1-year was 26.2% overall; it was lower among women with no/little treatment bother (25.7%, GP5 = 0-1) compared to moderate/high treatment bother prior to initiating anastrozole (34.7%, GP5 = 2-4; HR = 1.50, 95% confidence interval [CI]:1.04-2.15, p = 0.027). Subgroup analyses by racial cohort showed a similar predictive effect of GP5 in the White (n = 606, HR = 1.76, 95% CI: 1.12-2.77, p = 0.014) and Black (n = 184, HR = 1.85, 95% CI: 0.92-3.71, p = 0.079) cohorts, but not in the Asian cohort (n = 197, HR = 0.40, 95% CI: 0.10-1.62, p = 0.20). Conclusions: Moderate/high treatment bother prior to starting anastrozole was observed in 10% of patients and associated with a higher risk of early discontinuation, except in Asian patients. Our findings support the presence of a treatment tolerability threshold which can be compromised by pre-treatment burden. Treatment tolerability may also be influenced by cultural and genetic factors, which will be explored in further analysis of genetic and PRO data. Clinical trial information: NCT01824836.
Prospective validation of genetic predictors of aromatase inhibitor-associated musculoskeletal symptoms (AIMSS) in a racially diverse cohort: Results from ECOG-ACRIN E1Z11.
12003 Background: AIMSS are common and frequently lead to early discontinuation of adjuvant AI therapy. Single nucleotide polymorphisms (SNPs) in candidate genes have been associated with AIMSS and AI discontinuation. The primary objective of E1Z11 was to validate previously identified associations between 10 specific SNPs in candidate genes and AI discontinuation due to AIMSS in a community-based, racially diverse cohort. Methods: Postmenopausal women with hormone receptor-positive stage I-III breast cancer enrolled onto a prospective multi-site cohort study, the majority through the NCI Community Oncology Research Program (NCORP). Participants received anastrozole 1 mg oral daily, and completed patient-reported outcomes (PROs) at baseline, 3, 6, 9, and 12 months. AIMSS was defined as >20% increase in Stanford Health Assessment Questionnaire (HAQ) score over baseline occurring within 1 year of AI therapy. We projected 40% would develop AIMSS and 25% would discontinue AI treatment within 1 year, informing a planned enrollment of 1000 women with a fixed number per strata (600 Caucasian, 200 African-American [AA] & 200 Asian) to provide 80% power to detect an effect size of 1.5-4. SNPs include ESR1 (rs2234693, rs2347868, rs9340835), CYP19A1 (rs1062033, rs4646), TCL1A (rs11849538, rs2369049, rs7158782, rs7159713), and HTR2A (rs2296972). Hardy-Weinberg equilibrium (HWE) was evaluated within each racial subset. SNP genotypes were coded as additive effects on the log odds ratio by coding as 0, 1 or 2 for the count of the minor allele. A Cochran-Armitage trend test was used with a 1-sided alpha of 0.0025 (Bonferroni correction for 10 tests). Results: We enrolled 999 evaluable women (616 Caucasian, 184 AA, 199 Asian). Genotyping was successful in 974 (98%). AIMSS developed in 43%, and AI therapy was discontinued in 12% within 1 year. While more AA and Asians developed AIMSS compared to Caucasians (48% vs 38%, p=0.017; 50% vs 38%, p=0.004), AI discontinuation rates were similar across racial groups. HWE was satisfied for all SNPs at the 5% alpha level, except for TCL1A/rs11849538 (p=0.002) in the AA cohort. None of the 10 SNPs were significantly associated with AI discontinuation or development of AIMSS in the overall population, or in any of the 3 cohorts. Conclusions: Although AIMSS were more common in AA and Asians, AI discontinuation rates were similar in the 3 cohorts. We were unable to prospectively validate 10 SNPs in 4 genes previously associated with AI discontinuation due to AIMSS. Future analyses will include other predictors of AIMSS, PROs, and additional genetic markers for the entire cohort and by race. Support: NCI UG1CA189828, UG1CA233196, UG1CA233277, UG1CA233320, UG1CA233178, UG1CA233160, UG1CA232760, UG1CA233341, UG1CA233329, U10CA180821, UG1CA189821, UG1CA189830, U10CA180888, UG1CA189859, UG1CA189863, UG1CA189971. Clinical trial information: NCT01824836.
Organizing Online Health Content: Developing Hashtag Collections for Healthier Internet-Based People and Communities
Twitter use has increased among patients with cancer, advocates, and oncology professionals. Hashtags, a form of metadata, can be used to share content, organize health information, and create virtual communities of interest. Cancer-specific hashtags modeled on a breast cancer community, #bcsm, led to the development of a structured set of hashtags called the cancer tag ontology. In this article, we review how these hashtags have worked with the aim of describing our experience from 2011 to 2017. We discuss useful guidelines for the development and maintenance of health-oriented communities on Twitter, including possible challenges to community sustainability and opportunities for future improvement and research.
Disease-specific hashtags for online communication about cancer care.
The symptom burden of cancer: Evidence for a core set of cancer‐related and treatment‐related symptoms from the Eastern Cooperative Oncology Group Symptom Outcomes and Practice Patterns study
Integrating Patient-Reported Outcomes Into Cancer Symptom Management Clinical Trials Supported by the National Cancer Institute–Sponsored Clinical Trials Networks
Patient-reported outcomes (PROs) are often the primary end point in symptom management trials. The scientific field of PROs is evolving, as evidenced by the US Food and Drug Administration's February 2007 release of a draft guidance for using PROs in effectiveness claims for drug labeling. This article presents issues encountered during use of PROs in National Cancer Institute–sponsored symptom management trials. Selected trials are presented that exemplify the challenges often seen in symptom management trials, and solutions are described. The examples presented include defining the appropriate end point, selecting and validating assessments, and answering the research questions through statistical analysis and interpretation. Progress has been made in addressing some of the unique challenges of PRO-based symptom management research. Many challenges still remain, but a foundational body of work now exists for more consistent and rigorous application of PROs into symptom management trials. There remains a need for more research in several methodologic aspects of design, analysis, and interpretation of symptom management trials.
To Feed or Not to Feed: Is That the Right Question?