Introduction/objectives Many individuals with rheumatoid arthritis (RA) report persistent fatigue even after management of peripheral disease activity. This study used whole-brain magnetic resonance spectroscopic imaging (MRSI) to investigate whether abnormal inflammatory activity in the central nervous system may be associated with such symptoms. We hypothesized that RA patients would show higher brain choline (CHO), myo-inositol (MI), and lactate (LAC), and higher brain temperature than healthy controls. We further hypothesized that the metabolite levels would be positively correlated with self-reported fatigue. Method Thirteen women with RA provided fatigue severity ratings and underwent whole-brain MRSI and a joint examination. Thirteen healthy controls (HC) provided comparison imaging and fatigue data. CHO, MI, LAC, and brain temperature in 47 brain regions were contrasted between groups using independent-samples t tests. Significant differences were determined using a false discovery rate (FDR)-adjusted p value threshold of ≤ 0.0023. Secondary analyses obtained correlations between imaging and clinical outcomes in the RA group. Results No brain metabolic differences were identified between the groups. In the RA group, fatigue severity was positively correlated with CHO in several brain regions-most strongly the right frontal lobe (r s = 0.823, p < 0.001). MI was similarly correlated with fatigue, particularly in the right calcarine fissure (r s = 0.829, p < 0.001). CHO in several regions was positively correlated with joint swelling and tenderness. Conclusions We conclude that abnormal brain metabolites are not a common feature of RA, but may been seen in patients with persistent fatigue or disease activity after conventional treatment. Key Points • Whole-brain magnetic resonance spectroscopy revealed no metabolic abnormalities in the brain in patients with rheumatoid arthritis. • Brain choline levels were correlated with fatigue severity reported by RA patients and with peripheral joint swelling and tenderness. • Brain myo-inositol levels were similarly correlated with fatigue severity in RA patients.

Background: Evidence suggests that neurometabolic abnormalities can persist after traumatic brain injury (TBI) and drive clinical symptoms such as fatigue and cognitive disruption. Magnetic resonance spectroscopy has been used to investigate metabolite abnormalities following TBI, but few studies have obtained data beyond the subacute stage or over large brain regions. Objective: To measure whole-brain metabolites in chronic stages of TBI. Design: Observational study. Setting: University. Participants: Eleven men with a moderate or severe TBI more than 12 months prior and 10 age-matched healthy controls completed whole-brain spectroscopic imaging. Main Measures: Ratios of N-acetylaspartate (NAA), choline (CHO), and myoinositol (MI) to creatine (CR) were measured in whole-brain gray and white matter as well as 64 brain regions of interest. Arterial spin labeling (ASL) data were also collected to investigate whether metabolite abnormalities were accompanied by differences in cerebral perfusion. Results: There were no differences in metabolite ratios within whole-brain gray and white matter regions of interest (ROIs). Linear regression showed lower NAA/CR in the white matter of the left occipital lobe but higher NAA/CR in the gray matter of the left parietal lobe. Metabolite abnormalities were observed in several brain regions in the TBI group including the corpus callosum, putamen, and posterior cingulate. However, none of the findings survived correction for multiple comparison. There were no differences in cerebral blood flow between patients and controls. Conclusion: Higher MI/CR may indicate ongoing gliosis, and it has been suggested that low CHO/CR at chronic time points may indicate cell death or lack of healthy turnover and repair. However, with the small sample size of this study, we caution against the over interpretation of our results. None of the findings within ROIs survived correction for multiple comparison. Thus, they may be considered possible avenues for future research in this area.

Background: Biomarkers with robust analytical and clinical validity can help optimize therapy decisions within clinical trials for patients with breast cancer, particularly if some data on clinical utility also exist. However, little is known about how physicians enrolling in clinical trials view them. Physician comfort with the integral use of conventional and investigational biomarkers for reducing chemotherapy intensity within clinical trials is explored in this study. Method: A convenience sample of academic and community oncologists from across the United States were invited to participate in qualitative interviews that explored their perspectives on the use of biomarkers for the de-escalation of chemotherapy in patients with breast cancer. Purposive sampling techniques were used to identify participants, ensuring even distribution of gender, work setting, and time practicing medical oncology. Interviews were audio-recorded and transcribed. Transcripts were analyzed by two independent coders to identify major themes and exemplary quotes in NVivo. A framework for understanding how providers conceptualize biomarkers was created. Results: There was a total of 39 physicians with a median age of 50; 51% of physicians were academic and 49% were community-based. 44% of oncologists have been in practice for less than 15 years, and 36% and 20% of oncologists were in practice for 15-30 years and over 30 years, respectively. The model on physician level of comfort for biomarker use consisted of 1) standard of care biomarkers, 2) standard biomarkers in newer contexts, and 3) experimental biomarkers with inclusion of additional related subthemes. There was a shared theme among physicians that historical experience with a biomarker made them more comfortable in de-escalation of chemotherapy. The greatest level of physician comfort with biomarker for de-escalation of chemotherapy came with biomarkers used in standard of care (e.g., MammaPrint, Oncotype DX). Themes related to these biomarkers included: strong level of evidence, agreement with NCCN guidelines, and widespread use in the community. For example, one physician stated, “for me to use a prognostic biomarker … typically it’s going to have to at least be within the NCCN guidelines or out there”. Secondly, physicians expressed reasonable confidence with some reluctance in the use of standard of care biomarkers in contexts that differ from where they were initially tested (i.e., use of biomarker in patients with different features or disease biology). These themes included the use of biomarkers in specific subtypes of cancer and when there is less supportive evidence. One physician commented, “It’s just hard to analyze and really know whether [pathCR in ER+ setting] actually holds like it does for other tumor biologies”. There was more hesitation and least comfort with experimental biomarkers (e.g., tumor-infiltrating lymphocytes, circulating tumor DNA). For experimental biomarkers, physicians were primarily concerned with the quality and quantity of evidence supporting their use. Prospective trials were favored over retrospective; however, physicians were accepting if the retrospective study included a large sample, other biomarkers were used in conjunction, or multiple studies confirmed the results. Other themes that emerged regarding experimental biomarkers were their testing in diverse populations and reproducibility. Physicians expressed contentment with experimental biomarkers that were proven in “multiple big enough studies”, were “reproducible and not subjective”, and “demonstrate utility in the patient population that’s relevant”. Conclusion: Biomarkers can be divided into 3 successive levels: 1) standard of care biomarkers, 2) standard biomarkers in newer contexts, and 3) experimental biomarkers. Level of comfort concerning the use of biomarkers for de-escalation of chemotherapy is related to level of evidence for experimental biomarkers. Citation Format: Noon Eltoum, Halle thannickal, Nicole L. Henderson, Lynne I. Wagner, Lauren P. Wallner, Antonio C. Wolff, Gabrielle B. Rocque. The Hierarchy of Biomarkers [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-01-04.

349 Background: Biomarkers are regularly utilized to select treatment within cancer clinical trials. However, there remains a lack of understanding regarding physician perspectives on what data is needed for physicians to comfortably use these markers to escalate or de-escalate chemotherapy. Methods: Semi-structured qualitative interviews with medical oncologists from different academic and community-based cancer centers were conducted to investigate perspectives on the utilization of biomarkers to de-escalate chemotherapy. Key topics explored included: (1) physician preference for biology-based (e.g. genomic profiles) vs. response-based (e.g. complete pathologic response) biomarkers, and (2) importance of personal familiarity with biomarkers. Interviews were audio-recorded and transcribed. Two independent coders analyzed transcripts using a constant comparative method in NVivo to identify major themes. Analysis was stratified by practice-type to elucidate differences between oncologists at academic and community practices. Results: Of the 39 participating physicians, 51% practiced in an academic setting and 49% practiced in a community setting. The majority of physicians (67% overall, 77% community, 59% academic) did not have a preference for biology-based vs. response-based biomarkers, if the data is equally strong and clinical use is appropriate for the clinical context (e.g. patient subtype). Many physicians were reassured by achieving a real-time therapeutic response, with 23% of physicians preferring response-based biomarkers. One physician stated, “I am still more comfortable with a real-time, well-validated biomarker, response marker, than I am with an overall predictive marker for a population”. In contrast, 10% (all academic) preferred biology-based biomarkers. One physician commented “I think the biology is probably more attractive because that potentially allows you to avoid treatment, whereas pathCR they've already had to get treatment to get there”. The majority of academic physicians (55%) felt that strong data was more important than personal familiarity with regards to implementation of novel biomarkers, as noted by one who stated, “As long as there's good data, I don't care.” 15% of community physicians shared a similar view. The majority of community physicians (54%) voiced familiarity to be more important in their comfort with biomarker use as noted by one physician who stated, “I think things I’m already familiar with, I'm more inclined to feel good about”. 18% of academic physicians held a similar perspective. Conclusions: Academic and community physicians’ perspectives regarding use of novel biomarkers overlap, with multiple factors playing a role in how these biomarkers are used in decision-making. Future research is needed to understand the impact of biomarker selection on clinical trial enrollment.

Background Tumor biomarkers are regularly used to guide breast cancer treatment and clinical trial enrollment. However, there remains a lack of knowledge regarding physicians’ perspectives towards biomarkers and their role in treatment optimization, where treatment intensity is reduced to minimize toxicity. Methods Thirty-nine academic and community oncologists participated in semi-structured qualitative interviews, providing perspectives on optimization approaches to chemotherapy treatment. Interviews were audio-recorded, transcribed, and analyzed by 2 independent coders utilizing a constant comparative method in NVivo. Major themes and exemplary quotes were extracted. A framework outlining physicians’ conception of biomarkers, and their comfortability with their use in treatment optimization, was developed. Results In the hierarchal model of biomarkers, level 1 is comprised of standard-of-care (SoC) biomarkers, defined by a strong level of evidence, alignment with national guidelines, and widespread utilization. Level 2 includes SoC biomarkers used in alternative contexts, in which physicians expressed confidence, yet less certainty, due to a lack of data in certain subgroups. Level 3, or experimental, biomarkers created the most diverse concerns related to quality and quantity of evidence, with several additional modulators. Conclusion This study demonstrates that physicians conceptualize the use of biomarkers for treatment optimization in successive levels. This hierarchy can be used to guide trialists in the development of novel biomarkers and design of future trials.