Citations

AbstractWe studied 2,528 patients with upfront autologous haematopoietic cell transplantation (AHCT) for multiple myeloma (MM) from 2008–2017 to develop a prognostic model to predict outcomes. High‐risk cytogenetics included t(4;14), t(14;16), t(14;20), del13q on karyotype, del17p, +1q or 1pdel. A Cox model identified factors prognostic of progression/relapse in a training subset (n = 1,246). A weighted score using these factors was assigned to a validation cohort (n = 774). Presence of high‐risk cytogenetics [hazard ratio, (HR) 1·68 (1·3–2·17)] and pre‐AHCT bone marrow plasma cells (BMPCs) ≥10% [1·68 (1·33–2·12)] were assigned 4 points each; albumin at diagnosis <3·5 g/dl [1·31 (1·07–1·61)] 2; standard risk cytogenetics 1, and no cytogenetics abnormality, BMPCs <10% at AHCT and albumin ≥3·5 g/dl at diagnosis 0 points each. A three‐category system with low risk (0–3), intermediate risk (4–8) and high risk (9–10) showed 3‐year progression‐free survival in the low vs. intermediate vs. high risk of 58% (95% CI: 52–63) vs. 49% (95% CI: 43–56) vs. 31% (95% CI: 12–51), P < 0.001 respectively, and 3‐year OS in low vs. intermediate vs. high risk of 88% (95% CI: 84–91) vs. 81% (95% CI: 76–86) vs. 64% (95% CI: 39–80); P < 0·001. Our prognostic scoring system can identify MM patients at risk for early relapse after AHCT.

BackgroundThe association of community factors and outcomes after hematopoietic cell transplantation (HCT) has not been comprehensively described. Using the County Health Rankings and Roadmaps (CHRR) and the Center for International Blood and Marrow Transplant Research (CIBMTR), this study evaluated the impact of community health status on allogeneic HCT outcomes.MethodsThis study included 18,544 adult allogeneic HCT recipients reported to the CIBMTR by 170 US centers in 2014‐2016. Sociodemographic, environmental, and community indicators were derived from the CHRR, an aggregate community risk score was created, and scores were assigned to each patient (patient community risk score [PCS]) and transplant center (center community risk score [CCS]). Higher scores indicated less healthy communities. The impact of PCS and CCS on patient outcomes after allogeneic HCT was studied.ResultsThe median age was 55 years (range, 18‐83 years). The median PCS was –0.21 (range, –1.37 to 2.10; standard deviation [SD], 0.42), and the median CCS was –0.13 (range, –1.04 to 0.96; SD, 0.40). In multivariable analyses, a higher PCS was associated with inferior survival (hazard ratio [HR] per 1 SD increase, 1.04; 99% CI, 1.00‐1.08; P = .0089). Among hematologic malignancies, a tendency toward inferior survival was observed with a higher PCS (HR, 1.04; 99% CI, 1.00‐1.08; P = .0102); a higher PCS was associated with higher nonrelapse mortality (NRM; HR, 1.08; 99% CI, 1.02‐1.15; P = .0004). CCS was not significantly associated with survival, relapse, or NRM.ConclusionsPatients residing in counties with a worse community health status have inferior survival as a result of an increased risk of NRM after allogeneic HCT. There was no association between the community health status of the transplant center location and allogeneic HCT outcomes.

Abstract A data-independent acquisition (DIA) approach is being increasingly adopted as a promising strategy for identification and quantitation of proteomes. As most DIA data sets are acquired with wide isolation windows, highly complex MS/MS spectra are generated, which negatively impacts obtaining peptide information through classical protein database searches. Therefore, the analysis of DIA data mainly relies on the evidence of the existence of peptides from prebuilt spectral libraries. Consequently, one major weakness of this method is that it does not account for peptides that are not included in the spectral library, precluding the use of DIA for discovery studies. Here, we present a strategy termed Precursor ion And Small Slice-DIA (PASS-DIA) in which MS/MS spectra are acquired with small isolation windows (slices) and MS/MS spectra are interpreted with accurately determined precursor ion masses. This method enables the direct application of conventional spectrum-centric analysis pipelines for peptide identification and precursor ion-based quantitation. The performance of PASS-DIA was observed to be superior to both data-dependent acquisition (DDA) and conventional DIA experiments with 69 and 48% additional protein identifications, respectively. Application of PASS-DIA for the analysis of post-translationally modified peptides again highlighted its superior performance in characterizing phosphopeptides (77% more), N-terminal acetylated peptides (56% more), and N-glycopeptides (83% more) as compared to DDA alone. Finally, the use of PASS-DIA to characterize a rare proteome of human fallopian tube organoids enabled 34% additional protein identifications than DDA alone and revealed biologically relevant pathways including low abundance proteins. Overall, PASS-DIA is a novel DIA approach for use as a discovery tool that outperforms both conventional DDA and DIA experiments to provide additional protein information. We believe that the PASS-DIA method is an important strategy for discovery-type studies when deeper proteome characterization is required.

Introduction and objective: Onconephrology is a new and evolving field that deals with kidney complications in patients with cancer as well as the management of cancer in patients with preexisting kidney disease. With increasing numbers of patients with cancer with kidney-related complications, the field has garnered increased attention. Thus, an annual Greater Toronto Area Onconephrology Interest Group symposium was held in May 2019. The objective of the meeting was to demonstrate the junctures between oncology and nephrology by highlighting recent data regarding (1) kidney impairment in solid organ malignancies, (2) management and treatment of kidney cancer, (3) kidney impairment in hematologic malignancies, (4) malignancy and kidney transplantation, and (5) hyponatremia in patients with cancer. Methods and sources of information: Through a structured presentation, the group explored key topics discussed at a Kidney Disease Improving Global Outcomes (KDIGO) Controversies Conference on Onconephrology. Expert opinions, clinical trial findings, and publication summaries were used to illustrate patient and treatment-related considerations in onconephrology. Key findings: Kidney complications in patients with cancer are a central theme in onconephrology. An estimated 12% to 25% of patients with solid organ malignancies have chronic kidney disease (CKD), although in certain cancers, the prevalence of CKD is higher. Kidney impairment is also a common complication of some hematologic malignancies. The incidence of renal failure in patients with multiple myeloma is estimated at 18% to 56% and light chain cast nephropathy is seen in approximately 30% of these patients. In addition, there appears to be a bidirectional relationship between kidney cancer and CKD, with some data sets suggesting the risk increases as kidney function declines. Cancer is also of concern in patients with preexisting kidney disease. Kidney transplant recipients have a greater risk of cancer and a higher risk of cancer-related mortality. Kidney complications have also been associated with novel cancer therapies, such as immune checkpoint inhibitors and chimeric antigen receptor (CAR) T-cell therapy. An estimated 2% to 4% of patients initiating an immune checkpoint inhibitor may develop nephrotoxicity, whereas up to 40% of patients on CAR T-cell therapy experience cytokine release syndrome (CRS). Tumor lysis syndrome and electrolyte abnormalities, such as hyponatremia, have also been reported with CAR T-cell therapy. While the incidence and prevalence of hyponatremia vary depending on the cancer type and serum sodium cutoff point, hyponatremia may be seen in up to 46% of patients hospitalized in cancer centers. Conclusions: Onconephrology is a developing field and the themes arising from this meeting indicate a need for greater collaboration between oncologists and nephrologists. Educational symposia and onconephrology fellowship programs may allow for improved cancer care for patients with kidney disease.

Abstract Purpose: The role of immune-oncologic mechanisms of racial disparities in prostate cancer remains understudied. Limited research exists to evaluate the molecular underpinnings of immune differences in African American men (AAM) and European American men (EAM) prostate tumor microenvironment (TME). Experimental Design: A total of 1,173 radiation-naïve radical prostatectomy samples with whole transcriptome data from the Decipher GRID registry were used. Transcriptomic expressions of 1,260 immune-specific genes were selected to assess immune-oncologic differences between AAM and EAM prostate tumors. Race-specific differential expression of genes was assessed using a rank test, and intergene correlational matrix and gene set enrichment was used for pathway analysis. Results: AAM prostate tumors have significant enrichment of major immune-oncologic pathways, including proinflammatory cytokines, IFNα, IFNγ, TNFα signaling, ILs, and epithelial–mesenchymal transition. AAM TME has higher total immune content score (ICSHIGH) compared with 0 (37.8% vs. 21.9%, P = 0.003). AAM tumors also have lower DNA damage repair and are genomically radiosensitive as compared with EAM. IFITM3 (IFN-inducible transmembrane protein 3) was one of the major proinflammatory genes overexpressed in AAM that predicted increased risk of biochemical recurrence selectively for AAM in both discovery [HRAAM = 2.30; 95% confidence interval (CI), 1.21–4.34; P = 0.01] and validation (HRAAM = 2.42; 95% CI, 1.52–3.86; P = 0.0001) but not in EAM. Conclusions: Prostate tumors of AAM manifest a unique immune repertoire and have significant enrichment of proinflammatory immune pathways that are associated with poorer outcomes. Observed immune-oncologic differences can aid in a genomically adaptive approach to treating prostate cancer in AAM.

41 Background: Provider experience and physician burnout has been recognized as a critical issue in medicine. Ontario, Canada has a single payer cancer system run by Ontario Health (Cancer Care Ontario) with a mandate covering system level planning and delivery of cancer services, funding, and quality improvement. As part of a larger provincial initiative to address clinician burnout, we examined the prevalence and drivers of burnout in practicing physician oncologists in Ontario. Methods: In November-December 2019, surgical, medical, hematological, and radiation oncologists in Ontario were invited to complete an anonymous online survey to assess burnout and its drivers. Burnout prevalence was assessed through the Maslach Burnout Inventory – Human Services Survey for Medical Personnel (MBI-HSS MP). Data on demographic, workplace, engagement, and practice profiles were collected. Logistic regression modeling was conducted to assess key variables associated with “high” burnout using a common definition of high scores on the MBI subscales of emotional exhaustion (EE) (> 27) and/or depersonalization (DP) (>10). Results: Response rate to the survey was 44% (n=418) with 72% reporting high levels of burnout. Mean scores for EE (30.7, SD 12.1) and DP (9.9, SD 6.7) were consistent with high burnout. Participants endorsed known drivers of burnout including: 1) a poor culture of wellness at work (e.g., not comfortable talking to leadership (72%), 2) inefficiencies of practice (e.g. feeling insufficient documentation time (67%)) and 3) personal resilience (e.g. not feeling they are contributing professionally in ways they value (21%)). Age (<45yrs) (OR: 2.15), poor/marginal control over workload (OR: 4.42), feeling used/unappreciated (OR: 2.63), working atmosphere that feels hectic/chaotic (OR: 2.68), and insufficient time for documentation requirements (OR: 2.52) significantly impacted the odds of high burnout in the regression model (p<0.05). Conclusions: The high rate of burnout among oncology physicians in a single payer public cancer system in Ontario is concerning for the wellbeing of providers, patients and system sustainability. Drivers important for maintaining a culture of wellness and efficiency of practice will require local, regional and provincial health policy to improve. Next steps will include raising awareness with provincial initiatives/policy to address key burnout drivers, and examining the impact of working under pandemic conditions (Covid-19) on oncologist burnout.

Objective The diagnosis of autoimmune pancreatitis (AIP) is challenging. Sonographic and cross-sectional imaging findings of AIP closely mimic pancreatic ductal adenocarcinoma (PDAC) and techniques for tissue sampling of AIP are suboptimal. These limitations often result in delayed or failed diagnosis, which negatively impact patient management and outcomes. This study aimed to create an endoscopic ultrasound (EUS)-based convolutional neural network (CNN) model trained to differentiate AIP from PDAC, chronic pancreatitis (CP) and normal pancreas (NP), with sufficient performance to analyse EUS video in real time. Design A database of still image and video data obtained from EUS examinations of cases of AIP, PDAC, CP and NP was used to develop a CNN. Occlusion heatmap analysis was used to identify sonographic features the CNN valued when differentiating AIP from PDAC. Results From 583 patients (146 AIP, 292 PDAC, 72 CP and 73 NP), a total of 1 174 461 unique EUS images were extracted. For video data, the CNN processed 955 EUS frames per second and was: 99% sensitive, 98% specific for distinguishing AIP from NP; 94% sensitive, 71% specific for distinguishing AIP from CP; 90% sensitive, 93% specific for distinguishing AIP from PDAC; and 90% sensitive, 85% specific for distinguishing AIP from all studied conditions (ie, PDAC, CP and NP). Conclusion The developed EUS-CNN model accurately differentiated AIP from PDAC and benign pancreatic conditions, thereby offering the capability of earlier and more accurate diagnosis. Use of this model offers the potential for more timely and appropriate patient care and improved outcome.

Abstract Comparative outcomes of allogeneic hematopoietic cell transplantation (HCT) for BCR-ABL1− myeloproliferative neoplasms (MPNs) in blast phase (MPN-BP) vs de novo acute myeloid leukemia (AML), and AML with prior myelodysplastic syndromes (MDSs; post-MDS AML), are unknown. Using the Center for International Blood and Marrow Transplant Research (CIBMTR) database, we compared HCT outcomes in 177 MPN-BP patients with 4749 patients with de novo AML, and 1104 patients with post-MDS AML, using multivariate regression analysis in 2 separate comparisons. In a multivariate Cox model, no difference in overall survival (OS) or relapse was observed in patients with MPN-BP vs de novo AML with active leukemia at HCT. Patients with MPN-BP in remission had inferior OS in comparison with de novo AML in remission (hazard ratio [HR], 1.40 [95% confidence interval [CI], 1.12-1.76]) due to higher relapse rate (HR, 2.18 [95% CI, 1.69-2.80]). MPN-BP patients had inferior OS (HR, 1.19 [95% CI, 1.00-1.43]) and increased relapse (HR, 1.60 [95% CI, 1.31-1.96]) compared with post-MDS AML. Poor-risk cytogenetics were associated with increased relapse in both comparisons. Peripheral blood grafts were associated with decreased relapse in MPN-BP and post-MDS AML (HR, 0.70 [95% CI, 0.57-0.86]). Nonrelapse mortality (NRM) was similar between MPN-BP vs de novo AML, and MPN-BP vs post-MDS AML. Total-body irradiation–based myeloablative conditioning was associated with higher NRM in both comparisons. Survival of MPN-BP after HCT is inferior to de novo AML in remission and post-MDS AML due to increased relapse. Relapse-prevention strategies are required to optimize HCT outcomes in MPN-BP.