JCO oncology practice最新文献

Purpose: Despite evidence of diagnostic accuracy but unclear long-term clinical benefit, national utilization patterns of prostate-specific membrane antigen positron emission tomography (PSMA-PET) are undefined.

Methods: We conducted a serial cross-sectional study to evaluate the use of PET imaging among commercial insurance beneficiaries with prostate cancer using administrative claims from deidentified Blue Cross Blue Shield Axis database. Eligible patients included prevalent and incident prostate cancer cases. We calculated the proportions undergoing PET imaging in semiannual periods from January 1, 2016, through December 31, 2024. We examined the association between regional-level contextual sociodemographic and health care characteristics, and regional use of PSMA-PET imaging in 2024.

Results: A total of 514,750 male beneficiaries age 40-89 years with prostate cancer were identified between 2016 and 2024. The proportion of individuals with prostate cancer undergoing PET imaging increased from 4.5 [95% CI, 4.1 to 4.9] per 1,000 in the first half of 2016 to 77.6 (95% CI, 76.2 to 79.1) per 1,000 in the second half of 2024, P < .001. Increases in PET were driven by uptake of PSMA-PET following approval in 2021, which increased from 0.8 (95% CI, 0.6 to 0.9) per 1,000 in the second half of 2021 to 77.0 (95% CI, 75.5 to 78.5) per 1,000 in the second half of 2024, P < .001. PSMA-PET use in 2024 was higher in regions with greater education (99.3 v 114.6 per 1,000 in lowest [Q1] v highest [Q4] educated) and income (95.4 v 112.3 per 1,000 in Q1 v Q4 income) measures, P < .001.

Conclusion: PSMA-PET was rapidly incorporated into clinical practice among commercial insurance beneficiaries with prostate cancer with higher adoption in geographic regions with higher income and education.

Purpose: The classification of AML and therapeutic options are now largely driven by genetically defined subtypes. Personalization of treatment relies on timely completion and reporting of cytogenetic and molecular tests, creating challenges in clinical practice. We initiated a quality improvement study with the aim to optimize the process for ordering of genomic diagnostic tests and to reduce test turnaround times (TATs).

Methods: A multidisciplinary working group consisting of hematologists, laboratory scientists, technologists, and hematopathologists was formed and identified the following tests as necessary for expedited testing in patients with AML younger than 75 years: next-generation sequencing (NGS) myeloid panel, karyotype analysis, FLT3 PCR, NPM1 PCR, CBFB::MYH11 PCR, and RUNX1::RUNX1T1 PCR, and proposed a reflexive flow cytometry-triggered genomic diagnostic testing algorithm for newly diagnosed AML (ND-AML). We used the model of improvement and implemented three Plan-Do-Study-Act (PDSA) cycles: education and guidelines for management of ND-AML, implementation of the reflex laboratory-triggered diagnostic testing algorithm for ND-AML, and automation of NGS workflow. We assessed compliance with test ordering according to prescribed guidelines and TAT.

Results: After PDSA 2, test ordering improved significantly to more than 90% of relevant tests being initiated at AML diagnosis; and TAT was reduced by 27.6% for NGS and by 54.8% for NPM1 PCR. After PDSA 3, TAT for NGS was overall reduced by 63.3% to 11.4 days and within our 14-day target. We were able to also meet our target TAT of 5 days or less for FLT3 and NPM1 PCRs.

Discussion: A multidisciplinary approach with shared decision making between hematologists and laboratory practitioners was essential in the development of an algorithm for reflex testing in AML that resulted in improved test ordering and TAT.

Purpose: Goserelin is a gonadotropin-releasing hormone agonist for ovarian function suppression in the treatment of pre- and perimenopausal patients with breast cancer and for the preservation of ovarian function during chemotherapy. Goserelin is available in doses of 3.6 mg once every 4 weeks or 10.8 mg once every 12 weeks. This study used US real-world evidence to characterize goserelin treatment patterns.

Methods: Electronic health record data of adults with a history of breast cancer and ≥2 goserelin prescriptions between January 1, 2017, and December 31, 2022, were identified through TriNetX. Patient demographics and treatment patterns were examined.

Results: Overall, 3,620 US patients were identified: 2,870 treated with goserelin 3.6 mg once every 4 weeks, 410 treated with 10.8 mg once every 12 weeks, and 340 switched from 3.6 mg once every 4 weeks to 10.8 mg once every 12 weeks. Peak utilization of 10.8 mg once every 12 weeks (36.6%) and dose switching to 10.8 mg once every 12 weeks (26.5%) occurred in 2020. Patients who switched to 10.8 mg once every 12 weeks had the longest median treatment duration (776 days), compared with the 3.6 mg once every 4 weeks and 10.8 mg once every 12 weeks cohorts (264 and 429 days, respectively). Of patients who switched, 65% were still being treated after 2 years, compared with 30% and 40% treated with 3.6 mg once every 4 weeks only or 10.8 mg once every 12 weeks only, respectively. Patients initially treated with or who switched to 10.8 mg once every 12 weeks were more adherent (64.4%-75.0%), compared with patients treated with 3.6 mg once every 4 weeks (45.4%).

Conclusion: Treatment with goserelin 10.8 mg once every 12 weeks is associated with greater adherence and longer treatment duration, compared with 3.6 mg once every 4 weeks in patients with breast cancer in the United States.

Purpose: Little is known about guideline-concordant, early integration of palliative care (PC) in the outpatient setting among patients with advanced cancer within a safety-net system. This study examined PC delivery patterns for patients seen in a large, urban safety-net system.

Methods: Patients diagnosed with advanced-stage solid tumor and who had ≥1 outpatient oncology visit from January 2018 to July 2023 at Parkland Health were identified via electronic health record. Outcomes assessed included (1) receipt of PC referral ≤8 weeks after diagnosis, (2) receipt of any PC referral, and (3) PC visit completion. Multivariable logit models evaluated associations between key characteristics (age, race/ethnicity, gender, cancer type, preferred language, insurance, diagnosis year) and the outcomes.

Results: Among 1,296 patients (44% female; 76% non-White), 55% received a referral. Of those referred, 46% patients were referred early (≤8 weeks). Two thirds of the referred patients completed a PC visit during the study period. In adjusted regression models, patients who were Black (v White; adjusted odds ratio [aOR], 0.52 [95% CI, 0.33 to 0.82]), Hispanic (aOR, 0.33 [95% CI, 0.18 to 0.59]), or had prostate cancer (v breast cancer; aOR, 0.27 [95% CI, 0.10 to 0.69]) had lower odds of receiving early referral. Ages 40-69 (v >80 years; lowest odds for 60 to <70, aOR, 0.41 [95% CI, 0.20 to 0.85]) and patients with gynecologic cancer (aOR, 0.14 [95% CI, 0.07 to 0.28]) had lower odds of receiving any PC referral. Females had higher odds of completing a PC visit (v males; aOR, 1.45 [95% CI, 1.01 to 2.08]).

Conclusion: Many patients did not receive an outpatient referral or received it late. Observed differences by race/ethnicity, cancer type, and age suggest the need for different interventions targeting PC delivery for underserved patients with cancer.

Purpose: Adolescents and young adults (AYAs) with advanced cancer (AC) report poor quality of life (QOL), high psychological distress, and minimal engagement in health care discussions. We assessed the effect of a novel resilience coaching program (Promoting Resilience in Stress Management [PRISM]-AC) on AYA outcomes.

Methods: We conducted a multisite randomized trial of PRISM-AC versus usual care (UC) among AYAs age 12-24 years, diagnosed with AC within 2 weeks before enrollment. PRISM-AC consists of four sessions targeting AYA-endorsed resilience resources (stress management, goal-setting, cognitive reframing, and meaning-making) plus a session integrating elements of advance care planning. Participants completed surveys at baseline, and 3, 6, 9, and 12 months. The primary outcome was Pediatric QOL at 3 months; secondary/exploratory outcomes included 3-month changes in resilience (10-item Connor-Davidson Resilience Scale) and hope (Snyder Hope Scale), and trajectories of QOL, anxiety, and depression (Hospital Anxiety and Depression Scale) over 12 months. We examined associations with linear mixed effects regression models. We also explored PRISM-AC's impact on AYA participation in critical health care discussions, as documented in the electronic health record.

Results: Between April 2019 and January 2024, we enrolled 239 AYAs (56% of 426 approached) and randomly assigned 195 (82% of enrolled; 96 UC, 99 PRISM). They were of mean age 16.5 years (standard deviation, 3.9), mostly White (63%), non-Hispanic (59%), and publicly insured (53%). At 3 months, we detected no significant differences between groups with respect to QOL, anxiety, or depression; PRISM-AYAs demonstrated greater improvements in resilience (+1.3 [5.9] v -1.4 (7.5); P = .038) and hope (+2.4 [10.4] v -2.8 [11.2]; P = .001) than UC-AYAs. Over the 12-month study period, PRISM-AYAs reported more improvements in QOL and anxiety, with significant differences at later time points (PRISM-QOL improvements, 6 months: +3.4 [95% CI, 0.1 to 6.6]; P = .043; 12 months: +6.8 [95% CI, 3.3 to 10.3]; P < .001). Although participation in key health care discussions was similar between groups from baseline to 6 months, 67% (95% CI, 35 to 88) and 50% (95% CI, 22 to 78) of PRISM-AYAs participated at 9 and 12 months, respectively, compared with 39% (95% CI, 20 to 61) and 38% (95% CI, 21 to 59) of UC-AYAs.

Conclusion: Among AYAs with AC, PRISM-AC did not immediately improve QOL. Rather, it improved resilience and hope, potentially enabling longer-term improvements in QOL.

Purpose: The purpose of our study was to (1) use a large language model (LLM) to identify goals-of-care (GOC) conversations in a large volume of notes, and (2) explore the potential of LLMs for a novel summarization task.

Methods: We included patients diagnosed with advanced cancer between April 1, 2024, and June 30, 2024. A validated LLM prompt for GOC was applied to electronic health records (EHRs) using a Health Insurance Portability and Accountability Act (HIPPA)-secure version of GPT-4o, a LLM developed by OpenAI. Output included (1) presence or absence of GOC documentation, (2) explanations with source text used to inform the LLM's determination, and (3) a hallucination score, indicating proportion of source text generated by the LLM that did not perfectly match text in the EHR. Two LLM prompts were designed to generate structured and unstructured GOC summaries. We randomly selected five patients and applied the summarization task to notes flagged by LLM as containing GOC. We reviewed LLM summaries to examine for relevant information.

Results: Among 326 patients associated with nearly 1,400 clinical notes, LLM flagged approximately 40% of notes for GOC documentation. Subsequent review of explanation text identified that 128 patients (nearly 40% of the total patient population) had GOC documentation. The hallucination index for explanations was low, suggesting that the LLM did not produce text that was not found in EHRs. LLM prompts produced accurate summaries in less than 2 minutes per patient.

Conclusion: LLMs can capture GOC at scale and generate clinically useful summaries. Future directions include real-time implementation in the clinical setting.