Evaluating Options and Ethics in Pediatric Dentistry due to Declining Access to Hospital Operating Rooms

AbstractPediatric dentists rely on access to hospital operating rooms for safe, effective, and humane delivery of dental care. The children who benefit most from dental treatment in a hospital operating room are those who are very young, have dental anxieties or phobias, are precommunicative or noncommunicative, need extensive or invasive dental treatments, or have special healthcare needs. Diminishing access to hospital operating rooms for pediatric dental treatment has become an escalating problem in contemporary times. Financial barriers, hospital costs, reimbursement rates, health insurance policies and deductibles, out-of-network hospitals, socioeconomic factors, and the COVID-19 pandemic are prominent contributing factors. This problem in access to care has resulted in long waiting times for hospital operating rooms, deferral of medically necessary dental care, and pain and infection among this vulnerable patient population. Pediatric dentists have responded to the problem by utilizing alternative methods of care delivery, such as in-office deep sedation or in-office general anesthesia, and by implementing aggressive medical management of dental caries. However, the youngest of pediatric patients and children with special healthcare needs still remain at a disadvantage in receiving definitive dental treatment. This article aims to highlight the ethical challenges faced by pediatric dentists in contemporary practice in the face of limitations in hospital operating room access through four case scenarios.

Donor Genetic Predisposition to High Interleukin-10 Production Appears Protective against Acute Graft-Versus-Host Disease

The persistence of graft-versus-host disease (GVHD) as the principal complication of allogeneic hematopoietic cell transplantation (HCT) demonstrates that HLA matching alone is insufficient to prevent alloreactivity. We performed molecular and functional characterization of 22 candidate cytokine genes for their potential to improve matching in 315 myeloablative, 10/10 HLA-matched donor−recipient pairs. Recipients of a graft carrying the -1082GG IL10 gene promoter region variant had a three-fold lower incidence of grade II−IV acute GVHD compared to IL10-1082AA graft recipients (SHR = 0.25, p = 0.005). This was most evident in matched unrelated donor (MUD) transplants, where the greatest alloreactivity is expected. IL10-1082GG transplants did not experience an increased incidence of relapse, and, consequently, overall survival was two-fold higher in IL10-1082GG MUD transplants (HR = 0.17, p = 0.023). Longitudinal post-transplant measurements demonstrated that -1082GG is a high-IL10-producing and -expressing genotype with attenuated CD8+ T-cell reconstitution. High post-transplant donor chimerism in T- and myeloid-cells (>95%) confirmed a predominant donor, rather than recipient, genotype effect on immune function and aGVHD. To date, this is the first study to report corroborating genome-to-cellular evidence for a non-HLA donor immunogenetic variant that appears to be protective against GVHD. The incorporation of IL10 variants in donor selection criteria and clinical-management decisions has the potential to improve patient outcomes.

Incomplete chimerism following myeloablative and anti-thymocyte globulin-conditioned hematopoietic cell transplantation is a risk factor for relapse and chronic graft-versus-host disease

BACKGROUND AIMS

The value of routine chimerism determination after myeloablative hematopoietic cell transplantation (HCT) is unclear, particularly in the setting of anti-thymocyte globulin (ATG)-based graft-versus-host disease (GVHD) prophylaxis.

METHODS

Blood samples were collected at 3 months post-HCT from 558 patients who received myeloablative conditioning and ATG-based GVHD prophylaxis. Chimerism was assessed using multiplex polymerase chain reaction of short tandem repeats in sorted T cells (CD3+) and leukemia lineage cells (CD13+CD33+ for myeloid malignancies and CD19+ for B-lymphoid malignancies). ATG exposure was determined using a flow cytometry-based assay. The primary outcomes of interest were relapse and chronic GVHD (cGVHD).

RESULTS

Incomplete (<95%) T-cell chimerism and leukemia lineage chimerism were present in 17% and 4% of patients, respectively. Patients with incomplete T-cell chimerism had a significantly greater incidence of relapse (36% versus 22%, subhazard ratio [SHR] = 2.03, P = 0.001) and lower incidence of cGVHD (8% versus 25%, SHR = 0.29, P < 0.001) compared with patients with complete chimerism. In multivariate modeling, patients with high post-transplant ATG area under the curve and any cytomegalovirus (CMV) serostatus other than donor/recipient seropositivity (non-D+R+) had an increased likelihood of incomplete T-cell chimerism. Patients with incomplete leukemia lineage chimerism had a significantly greater incidence of relapse (50% versus 23%, SHR = 2.70, P = 0.011) and, surprisingly, a greater incidence of cGVHD (45% versus 20%, SHR = 2.64, P = 0.003).

CONCLUSIONS

High post-transplant ATG exposure and non-D+R+ CMV serostatus predispose patients to incomplete T-cell chimerism, which is associated with an increased risk of relapse. The increased risk of cGVHD with incomplete B-cell/myeloid chimerism is a novel finding that suggests an important role for recipient antigen-presenting cells in cGVHD pathogenesis.

StarGazer: A Hybrid Intelligence Platform for Drug Target Prioritization and Digital Drug Repositioning Using Streamlit

Target prioritization is essential for drug discovery and repositioning. Applying computational methods to analyze and process multi-omics data to find new drug targets is a practical approach for achieving this. Despite an increasing number of methods for generating datasets such as genomics, phenomics, and proteomics, attempts to integrate and mine such datasets remain limited in scope. Developing hybrid intelligence solutions that combine human intelligence in the scientific domain and disease biology with the ability to mine multiple databases simultaneously may help augment drug target discovery and identify novel drug-indication associations. We believe that integrating different data sources using a singular numerical scoring system in a hybrid intelligent framework could help to bridge these different omics layers and facilitate rapid drug target prioritization for studies in drug discovery, development or repositioning. Herein, we describe our prototype of the StarGazer pipeline which combines multi-source, multi-omics data with a novel target prioritization scoring system in an interactive Python-based Streamlit dashboard. StarGazer displays target prioritization scores for genes associated with 1844 phenotypic traits, and is available via https://github.com/AstraZeneca/StarGazer.

Accurate Step Count with Generalized and Personalized Deep Learning on Accelerometer Data

Physical activity (PA) is globally recognized as a pillar of general health. Step count, as one measure of PA, is a well known predictor of long-term morbidity and mortality. Despite its popularity in consumer devices, a lack of methodological standards and clinical validation remains a major impediment to step count being accepted as a valid clinical endpoint. Previous works have mainly focused on device-specific step-count algorithms and often employ sensor modalities that may not be widely available. This may limit step-count suitability in clinical scenarios. In this paper, we trained neural network models on publicly available data and tested on an independent cohort using two approaches: generalization and personalization. Specifically, we trained neural networks on accelerometer signals from one device and either directly applied them or adapted them individually to accelerometer data obtained from a separate subject cohort wearing multiple distinct devices. The best models exhibited highly accurate step-count estimates for both the generalization (96-99%) and personalization (98-99%) approaches. The results demonstrate that it is possible to develop device-agnostic, accelerometer-only algorithms that provide highly accurate step counts, positioning step count as a reliable mobility endpoint and a strong candidate for clinical validation.

OSPred Tool: A Digital Health Aid for Rapid Predictive Analysis of Correlations Between Early End Points and Overall Survival in Non-Small-Cell Lung Cancer Clinical Trials

Overall survival (OS) is the gold standard end point for establishing clinical benefits in phase III oncology trials. However, these trials are associated with low success rates, largely driven by failure to meet the primary end point. Surrogate end points such as progression-free survival (PFS) are increasingly being used as indicators of biologic drug activity and to inform early go/no-go decisions in oncology drug development. We developed OSPred, a digital health aid that combines actual clinical data and machine intelligence approaches to visualize correlation trends between early (PFS-based) and late (OS) end points and provide support for shared decision making in the drug development pipeline.

Impact of FLT3 internal tandem duplication and NPM1 mutations in acute myeloid leukemia treated with allogeneic hematopoietic cell transplantation

BACKGROUND AIMS

The internal tandem duplication of FLT3 (FLT3^ITD) and NPM1 mutations (NPM1^mut) are well-established prognostic factors in cytogenetically intermediate-risk acute myeloid leukemia (AML) when treated with chemotherapy alone. However, their prognostic value in the setting of allogeneic hematopoietic cell transplantation (HCT) is controversial.

METHODS

FLT3 and NPM1 mutational status was determined at diagnosis using single-gene polymerase chain reaction or next-generation sequencing in 247 adult patients with cytogenetically intermediate-risk AML who underwent myeloablative HCT. Multivariate Fine-Gray and Cox regression was used to analyze the cumulative incidence of relapse (CIR), relapse-free survival (RFS) and overall survival (OS).

RESULTS

FLT3^ITD and NPM1^mut were present in 74 of 247 (30%) and 79 of 247 (32%) patients, respectively. There was no significant difference between patients without a FLT3^ITD or NPM1^mut (FLT3^NONITD/NPM1^WT) and patients with a FLT3^ITD mutation alone (FLT3^ITD/NPM1^WT) with regard to CIR (P = 0.60), RFS (P = 0.91) or OS (P = 0.66). Similarly, there was no significant difference between FLT3^NONITD/NPM1^WT and FLT3^NONITD/NPM1^mut patients with regard to CIR (P = 0.70), RFS (P = 0.75) or OS (P = 0.95). The presence of a concurrent mutation in NPM1 did not appear to modify the impact of having a FLT3^ITD mutation.

CONCLUSIONS

In contrast to chemotherapy-only treatment, FLT3 and NPM1 mutational status does not appear to predict outcomes in patients with cytogenetically intermediate-risk AML following HCT. These results suggest that HCT may ameliorate the poor prognostic effect of FLT3^ITD mutation and that HCT should be considered over chemotherapy-only treatment in FLT3^ITD-mutated AML.

Analysis of Use and Outcomes of the Balance Digital Disease Management Tool for Patients with Type 2 Diabetes

Management of type 2 diabetes mellitus (T2DM) is a serious medical need for millions of patients and clinicians worldwide. Numerous smartphone apps for T2DM management are available. Due to their global accessibility, computing power and cellular connectivity, the pervasiveness of mobile phones now provide an opportunity for non-invasive Digital Therapeutics that have the potential to manage disease by modifying patient behavior as new modality for disease management and intervention. However, this novel approach has yet to be tested in large clinical studies. The BALANCE clinical study was designed to evaluate mobile phone App usage in a large multi-center clinical trial and its impact on T2DM outcomes. It included a digital aid for the management of, blood glucose, diet, physical activity, and medication adherence. Overall, patient use of the BALANCE-App was low (21% of significant patients users), and it diminished over time. BALANCE showed no effect on HbA1c or weight, what is consistent with other smartphone apps for T2DM which were tested on large clinical trials. Nevertheless, post-hoc subgroup analysis showed women using the App significantly achieved a significant reduction in HbA1c and weight.Clinical relevance Suitability of Digital Therapeutics, at least in the form of smartphone apps, for T2DM is under question. The low use indicates need for a strong focus in patient acceptability and patient engagement in the design process.

A biomarker-guided, prospective, phase 2 trial of pre-emptive graft-versus-host disease therapy using anti-thymocyte globulin

BACKGROUND AIMS

Intensified immunosuppressive prophylaxis for graft-versus-host disease (GVHD) may be toxic and therefore warranted only in patients at high risk of developing GVHD. In patients who underwent allogeneic hematopoietic cell transplant at the authors' center, high serum soluble IL-2 receptor alpha (sIL-2Rα) and low IL-15 levels on day 7 post-transplant were found to predict a high risk of developing clinically significant GVHD (sGVHD), defined as grade 2-4 acute GVHD or moderate to severe chronic GVHD.

METHODS

This was a prospective, phase 2 trial in which high-risk patients (serum sIL-2Rα >4500 ng/L or IL-15 <31 ng/L) received rabbit anti-thymocyte globulin (ATG) 3 mg/kg on day 8 post-transplant. Controls consisted of patients who had their sIL-2Rα/IL-15 levels measured but did not participate in the trial. A total of 68 trial patients and 143 controls were accrued to this study. The primary endpoint was incidence of sGVHD.

RESULTS

There was a reduction in sGVHD in high-risk trial patients (received day 8 ATG) compared with high-risk controls (did not receive day 8 ATG) (sub-hazard ratio [SHR] = 0.48, P < 0.05). There was no significant difference between the groups in overall survival or relapse; however, there was a greater incidence of non-GVHD-associated non-relapse mortality in high-risk trial patients (SHR = 3.73, P < 0.05), mostly related to infections. This may be due in part to the biomarkers ineffectively stratifying GVHD risk.

CONCLUSIONS

Pre-emptive ATG therapy is both feasible and effective at reducing sGVHD without increasing relapse. Further mitigation strategies are needed to reduce the risk of infection associated with intensified GVHD prophylaxis. This study was registered at ClinicalTrials.gov (NCT01994824).

Correlation Between Early Endpoints and Overall Survival in Non-Small-Cell Lung Cancer: A Trial-Level Meta-Analysis

Early endpoints, such as progression-free survival (PFS), are increasingly used as surrogates for overall survival (OS) to accelerate approval of novel oncology agents. Compiling trial-level data from randomized controlled trials (RCTs) could help to develop a predictive framework to ascertain correlation trends between treatment effects for early and late endpoints. Through trial-level correlation and random-effects meta-regression analysis, we assessed the relationship between hazard ratio (HR) OS and (1) HR PFS and (2) odds ratio (OR) PFS at 4 and 6 months, stratified according to the mechanism of action of the investigational product. Using multiple source databases, we compiled a data set including 81 phase II-IV RCTs (35 drugs and 156 observations) of patients with non-small-cell lung cancer. Low-to-moderate correlations were generally observed between treatment effects for early endpoints (based on PFS) and HR OS across trials of agents with different mechanisms of action. Moderate correlations were seen between treatment effects for HR PFS and HR OS across all trials, and in the programmed cell death-1/programmed cell death ligand-1 and epidermal growth factor receptor trial subsets. Although these results constitute an important step, caution is advised, as there are some limitations to our evaluation, and an additional patient-level analysis would be needed to establish true surrogacy.

COVID-19 infection among international travellers: a prospective analysis

OBJECTIVES

This report estimates the risk of COVID-19 importation and secondary transmission associated with a modified quarantine programme in Canada.

DESIGN AND PARTICIPANTS

Prospective analysis of international asymptomatic travellers entering Alberta, Canada.

INTERVENTIONS

All participants were required to receive a PCR COVID-19 test on arrival. If negative, participants could leave quarantine but were required to have a second test 6 or 7 days after arrival. If the arrival test was positive, participants were required to remain in quarantine for 14 days.

MAIN OUTCOME MEASURES

Proportion and rate of participants testing positive for COVID-19; number of cases of secondary transmission.

RESULTS

The analysis included 9535 international travellers entering Alberta by air (N=8398) or land (N=1137) that voluntarily enrolled in the Alberta Border Testing Pilot Programme (a subset of all travellers); most (83.1%) were Canadian citizens. Among the 9310 participants who received at least one test, 200 (21.5 per 1000, 95% CI 18.6 to 24.6) tested positive. Sixty-nine per cent (138/200) of positive tests were detected on arrival (14.8 per 1000 travellers, 95% CI 12.5 to 17.5). 62 cases (6.7 per 1000 travellers, 95% CI 5.1 to 8.5; 31.0% of positive cases) were identified among participants that had been released from quarantine following a negative test result on arrival. Of 192 participants who developed symptoms, 51 (26.6%) tested positive after arrival. Among participants with positive tests, four (2.0%) were hospitalised for COVID-19; none required critical care or died. Contact tracing among participants who tested positive identified 200 contacts; of 88 contacts tested, 22 were cases of secondary transmission (14 from those testing positive on arrival and 8 from those testing positive thereafter). SARS-CoV-2 B.1.1.7 lineage was not detected in any of the 200 positive cases.

CONCLUSIONS

21.5 per 1000 international travellers tested positive for COVID-19. Most (69%) tested positive on arrival and 31% tested positive during follow-up. These findings suggest the need for ongoing vigilance in travellers testing negative on arrival and highlight the value of follow-up testing and contact tracing to monitor and limit secondary transmission where possible.

Efficacy of Allogeneic Hematopoietic Cell Transplantation for Autoimmune Diseases

Allogeneic hematopoietic cell transplantation (HCT) may be efficacious for autoimmune diseases (AIDs), but its efficacy for individual AIDs is unknown. Factors influencing the likelihood of relapse for each AID are also unknown. This study aimed to determine the likelihood of relapse for each common AID and to generate hypotheses about factors influencing the likelihood of relapse. We reviewed charts of adult patients with nonhematologic AIDs who had undergone HCT in Alberta (n = 21) and patients described in the literature (n = 67). We used stringent inclusion criteria to minimize the inclusion of patients whose AID may have been cured before transplantation. We also used stringent definitions of AID relapse and remission. AID relapsed in 2 of 9 patients (22%) with lupus, in 4 of 12 (33%) with rheumatoid arthritis (RA), in 0 of 4 (0%) with systemic sclerosis (SSc), in 3 of 16 (19%) with psoriasis, in 1 of 12 (8%) with Behçet's disease (BD), in 1 of 15 (7%) with Crohn's disease (CD), in 0 of 5 (0%) with ulcerative colitis (UC), in 4 of 8 (50%) with multiple sclerosis (MS), and in 3 of 3 (100%) with type 1 diabetes mellitus (T1DM). Among highly informative patients (followed for >1 year after discontinuation of immunosuppressive therapy if no relapse, or donor AID status known if relapse), relapse occurred in 0 of 3 patients with lupus, in 2 of 7 with RA, in 0 of 2 with SSc, in 3 of 6 with psoriasis, in 0 of 3 with BD, in 0 of 10 with CD, in 0 of 3 with UC, in 2 of 3 with MS, and in 2 of 2 with T1DM. There appeared to be no associations between AID relapse and low intensity of pretransplantation chemoradiotherapy, multiple lines of AID therapy (surrogate for AID refractoriness) except perhaps for lupus, absence of serotherapy for graft-versus-host disease (GVHD) prophylaxis, lack of GVHD except perhaps for lupus, or incomplete donor chimerism. Even though remission commonly occurs after HCT in lupus, RA, SSc, psoriasis, BD, CD, and UC, HCT is efficacious for only a subset of patients. The efficacy appears to be unrelated to pretransplantation therapy, GVHD, or chimerism. Large studies are needed to determine the characteristics of patients likely to benefit from HCT for each AID.

Impaired natural killer cell counts and cytolytic activity in patients with severe COVID-19

The global pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-driven coronavirus disease 2019 (COVID-19) has caused unprecedented human death and has seriously threatened the global economy. Early data suggest a surge in proinflammatory cytokines in patients with severe COVID-19, which has been associated with poor outcomes. We recently postulated that the inflammatory response in patients with severe COVID-19 disease is not inhibited by natural killer (NK) cells, resulting in a "cytokine storm." Here, we assessed the NK-cell functional activity and the associated cytokines and soluble mediators in hospitalized COVID-19 patients. Significantly impaired NK-cell counts and cytolytic activity were observed in COVID-19 patients when compared with healthy controls. Also, cytokines like interleukin 12 (IL12), IL15, and IL21 that are important for NK-cell activity were not detected systematically. Serum concentrations of soluble CD25 (sCD25)/soluble IL2 receptor α (sIL2-Rα) were significantly elevated and were inversely correlated with the percentage of NK cells. Impaired NK-cell cytolytic activity together with other laboratory trends including elevated sCD25 were consistent with a hyperinflammatory state in keeping with macrophage-activation syndrome. Our findings suggest that impaired counts and cytolytic activity of NK cells are important characteristics of severe COVID-19 and can potentially facilitate strategies for immunomodulatory therapies.

Assessment of Objectively Measured Physical Activity as an Independent Estimator of Functional Status in Clinical Trials

Functional status of patients is an important concept in clinical trials. It subsumes functional capacity, which is traditionally estimated by exercise tests, and functional performance, which is often estimated by questionnaires. Objectively measured physical activity by means of wearables devices containing accelerometers (PA) have recently been proposed as a novel and advantageous way to estimate physical status including capacity and performance. There is nonetheless insufficient evidence of the association between PA and traditional ways to estimate functional status. In the ACTIVATE clinical trial, cycle ergometry tests were performed multiple times in all 267 patients, PA was measured for a week prior to each cycle ergometry test, and questionnaires were answered daily during the same week. Pearson's correlation tests and clustering analysis revealed that PA, physical activity experience as assessed by questionnaires, and exercise endurance time as measured by the cycle ergometry test, are largely independent. Therefore, all three approaches together might achieve a complete assessment of the functional status of patients in clinical trials, as they each independently correlate with health-related quality of life and important clinical outcomes such as hospitalizations but are weakly associated among themselves.

Hematopoietic cell transplant outcomes after myeloablative conditioning with fludarabine, busulfan, low-dose total body irradiation, and rabbit antithymocyte globulin

Optimal conditioning and graft-vs-host disease (GVHD) prophylaxis for hematopoietic cell transplantation (HCT) are unknown. Here, we report on outcomes after low toxicity, myeloablative conditioning consisting of fludarabine, busulfan, and 4 Gy total body irradiation, in combination with thymoglobulin and post-transplant methotrexate and cyclosporine. We retrospectively studied 700 patients with hematologic malignancies who received blood stem cells from 7 to 8/8 HLA-matched unrelated or related donors. Median follow-up of surviving patients was 5 years. At 5 years, overall survival (OS), relapse-free survival (RFS), and chronic GVHD/relapse-free survival (cGRFS) were 58%, 55%, and 40%. Risk factors for poor OS, RFS, and cGRFS were (1). high to very high disease risk index (DRI), (2). high recipient age, and (3). cytomegalovirus (CMV)-seropositive recipient with seronegative donor (D-R+). The latter risk factor applied particularly to patients with lymphoid malignancies. Neither donor other than HLA-matched sibling (7-8/8 unrelated) nor one HLA allele mismatch was risk factors for poor OS, RFS, or cGRFS. In conclusion, the above regimen results in excellent long-term outcomes. The outcomes are negatively impacted by older age, high or very high DRI, and CMV D-R+ serostatus, but not by donor unrelatedness or one HLA allele mismatch.

Curability and transferability of atopy with allogeneic hematopoietic cell transplantation

Atopy is excessive production of IgE in response to allergens. We evaluated in patients undergoing allogeneic hematopoietic cell transplantation (HCT) the following hypotheses: (1) Atopy is "curable" in atopic patients receiving HCT from a nonatopic donor (D-R+), and (2) Atopy is transferable from atopic donors to nonatopic recipients (D+R-). Atopic patients with atopic donors (D+R+) and non-atopic patients with non-atopic donors (D-R-) served as controls. We measured levels of multiallergen-specific IgE (A-IgE, atopy defined as ≥0.35 kU_A/L) in sera from 54 patients and their donors pre HCT and from the patients at ≥2 years post HCT. Only 7/12 (58%) D- R+ patients became nonatopic after HCT. Only 1/11 (9%) D+R- patients became atopic. Eleven of 13 (85%) D-R- patients remained nonatopic. Unexpectedly, 11/18 (61%) D+R+ patients became nonatopic. In conclusion, contrary to our hypothesis and previous reports, the "cure" of atopy may occur in only some D-R+ patients and the transfer of atopy may occur rarely. The "cure" may not be necessarily due to the exchange of atopic for nonatopic immune system, as the "cure" may also occur in D+R+ patients.

Comparison of abacavir-specific effector and proliferating functions of CD8 T cells in abacavir-treated HIV-1 patients

Susceptibility to abacavir hypersensitivity (ABH) in HIV-1-positive patients is strongly linked to the carriage of HLA-B*57:01 and the potential mechanism includes drug-specific activation of cytokine producing CD8 T cells exclusively in individuals carrying HLA-B*57:01. Here, we report a detailed characterization of abacavir-induced functional response of CD8 T cells in HLA-B*57:01^pos individuals. Peripheral blood mononuclear cells (PBMNCs) from HLA-B*57:01^pos ABH^pos and HLA-B*57:01^neg ABH^neg individuals were stimulated with abacavir. Multicolor flow cytometry was performed to assess the cytokine (IFNγ) production and degranulation (CD107a expression) after 6-18 hr culture and to enumerate proliferating CD4/CD8 T cells by culturing carboxyfluorescein diacetate succinimidyl ester-loaded PBMNCs for 7 days. CD8 T cells from HLA-B*57:01^pos ABH^pos individuals were multifunctional: proliferating, IFNγ producing, degranulating (CD107a^pos ), and both degranulating and IFNγ producing (CD107a^pos IFNγ^pos ). Degranulating CD8 T cells in general and both degranulating and IFNγ producing CD8 T cells in particular dominated abacavir-specific immune response. All functional responses were partially blocked by addition of HLA-B*57:01-reactive Bw4 mAb, but not by non-HLA-B*57:01-reactive Bw6 mAb. In conclusion, the study demonstrates that abacavir-specific CD8 T-cell-restricted immune response in HLA-B*57:01^pos ABH^pos HIV-1 patients has multiple effector and proliferating functions, where the primary effector response appears to be the release of cytolytic granules. The findings have implications for immunotherapy of HLA-related drug hypersensitivities.

Comparison of sequence-specific oligonucleotide probe vs next generation sequencing for HLA-A, B, C, DRB1, DRB3/B4/B5, DQA1, DQB1, DPA1, and DPB1 typing: Toward single-pass high-resolution HLA typing in support of solid organ and hematopoietic cell transplant programs

Many clinical laboratories supporting solid organ transplant programs use multiple HLA genotyping technologies, depending on individual laboratory needs. Sequence‐specific primers and quantitative polymerase chain reaction (qPCR) serve the rapid turnaround necessary for deceased donor workup, while sequence‐specific oligonucleotide probe (SSOP) technology is widely employed for higher volumes. When clinical need mandates high‐resolution data, Sanger sequencing‐based typing (SBT) has been the “gold standard.” However, all those methods commonly yield ambiguous typing results that utilize valuable laboratory resources when resolution is required. In solid organ transplantation, high‐resolution typing may provide critical information for highly sensitized patients with donor‐specific anti‐HLA antibodies (DSA), particularly when DSA involve HLA alleles not discriminated by SSOP typing. Arguments against routine use of SBT include assay complexity, long turnaround times (TAT), and increased costs. Here, we compare a next generation sequencing (NGS) technology with SSOP for accuracy, effort, turnaround time, and level of resolution for genotyping of 11 HLA loci among 289 specimens from five clinical laboratories. Results were concordant except for SSOP misassignments in eight specimens and 21 novel sequences uniquely identified by NGS. With few exceptions, SSOP generated ambiguous results while NGS provided unambiguous three‐field allele assignments. For complete HLA genotyping of up to 24 samples by either SSOP or NGS, bench work was completed on day 1 and typing results were available on day 2. This study provides compelling evidence that, although not viable for STAT typing of deceased donors, a single‐pass NGS HLA typing method has direct application for solid organ transplantation.

Rabbit Antithymocyte Globulin Serum Levels: Factors Impacting the Levels and Clinical Outcomes Impacted by the Levels

Antithymocyte globulin (ATG) levels and clearance vary significantly among patients receiving the same weight-based dose of ATG. To date, ATG area under the curve (AUC), its determinants, and its impact on clinical outcomes have been examined in pediatric hematopoietic cell transplant (HCT) and adult nonmyeloablative HCT. Here we set out to examine ATG AUC in 219 uniformly treated adults undergoing myeloablative allogeneic HCT at our institution. Sera were collected for the determination of pre- or post-HCT ATG AUC. The lowest quintiles of pre- and post-HCT AUC were associated with inferior chronic graft-versus-host disease (GVHD) and relapse-free survival (cGRFS) and a higher risk of acute GVHD, respectively. The highest pre- or post-HCT ATG AUC quintiles were not associated with risk of death, nonrelapse mortality, or relapse. Factors most strongly associated with AUC were day -2 recipient absolute lymphocyte count, body mass index (BMI), and graft lymphocyte content. To achieve ideal pre-HCT AUC (avoiding low AUC to maximize cGRFS) in this HCT setting, ATG dosing will need to take into consideration recipient weight, BMI, and blood and graft lymphocyte counts. Further studies are required to develop a modern ATG dosing schema and to demonstrate that adjusting ATG dose to target a particular AUC is feasible and leads to improved outcomes.

Comparing Immunofluorescent versus H&E Glandular Architecture Features in Prognostic Models from Prostate Biopsies

Determining the best treatment for prostate cancer patients with a newly diagnosed positive biopsy can be challenging. Multivariate prognostic models are often employed to stratify patients into risk populations. Many models leverage quantitative features derived from morphological analysis of the tumor architecture in the biopsy specimen. The vast majority of these features are derived from analyzing standard hematoxylin and eosin (H&E) images. Immunofluorescence (IF) image analysis of tissue pathology has also recently been proven to be robust. In this work, we constructed multivariate models for prostate cancer prognosis comparing the usage of previously published IF vs H&E features. In images from 304 patients, the IF features prognostically outperform the H&E features. The IF feature model also exhibits consistent training vs validation performance, an important consideration when developing models subject to regulatory oversight. This paper presents the first evaluation of comparing previously published H&E and IF morphological features head-to-head in prognostic models from prostate biopsies.

Development and validation of a novel automated Gleason grade and molecular profile that define a highly predictive prostate cancer progression algorithm-based test

BACKGROUND

Postoperative risk assessment remains an important variable in the effective treatment of prostate cancer. There is an unmet clinical need for a test with the potential to enhance the Gleason grading system with novel features that more accurately reflect a personalized prediction of clinical failure.

METHODS

A prospectively designed retrospective study utilizing 892 patients, post radical prostatectomy, followed for a median of 8 years. In training, using digital image analysis to combine microscopic pattern analysis/machine learning with biomarkers, we evaluated Precise Post-op model results to predict clinical failure in 446 patients. The derived prognostic score was validated in 446 patients. Eligible subjects required complete clinical-pathologic variables and were excluded if they had received neoadjuvant treatment including androgen deprivation, radiation or chemotherapy prior to surgery. No patients were enrolled with metastatic disease prior to surgery. Evaluate the assay using time to event concordance index (C-index), Kaplan-Meier, and hazards ratio.

RESULTS

In the training cohort (n = 306), the Precise Post-op test predicted significant clinical failure with a C-index of 0.82, [95% CI: 0.76-0.86], HR:6.7, [95% CI: 3.59-12.45], p < 0.00001. Results were confirmed in validation (n = 284) with a C-index 0.77 [95% CI: 0.72-0.81], HR = 5.4, [95% CI: 2.74-10.52], p < 0.00001. By comparison, a clinical feature base model had a C-index of 0.70 with a HR = 3.7. The Post-Op test also re-classified 58% of CAPRA-S intermediate risk patients as low risk for clinical failure.

CONCLUSIONS

Precise Post-op tissue-based test discriminates low from intermediate high risk prostate cancer disease progression in the postoperative setting. Guided by machine learning, the test enhances traditional Gleason grading with novel features that accurately reflect the biology of personalized risk assignment.

Interval Kernels for Combining Biometric Measurements from Multiple Prostate Samples per Patient in Prognostic Models with Transductive Semi-Supervised Support Vector Regression

Prostate cancer is the most prevalent form of cancer and second most common form of cancer deaths among men in the United States. Physicians work with patients to make difficult treatment decisions. They are often aided by a multitude of prognostic models to assess risk and predict outcomes. These survival analysis models may analyze features characterizing biomolecular and histomorphic properties of the solid tumor sample. Commonly, multiple samples per patient are analyzed and features are combined in some way to generate a single result, such as by taking the median measurement. Recently, support vector regression approaches paired with a semi-supervised transduction framework have proven powerful in building such prognostic models. Separately, there has been work presenting the use of interval kernels to capture the range of measurements across multiple samples as an "interval" via the Hausdorff distance within a kernel based support vector approach. This paper presents the first results in exploring a combination of these two concepts. Namely, using an interval kernel based support vector approach within the aforementioned transduction framework to build prognostic models leveraging information from multiple tumor samples per patient. The results show that interval kernels yield more accurate prognostic models, and the semi-supervised transduction framework further improves performance. This suggests that this novel combination of unique recent advances can help build better prognostic models and improve the treatment of prostate cancer.

Impact of prostate biopsy tumor amount on imaging based prognostics employing transductive semi-supervised regression

For newly diagnosed prostate cancer patients with a positive biopsy, there are a variety of treatment options to consider. To aid physicians and patients in their decision making, a variety of predictive assays have emerged within the last decade, many of them imaging based. These assays build predictive models for survival analysis to provide personalized risk assessments for the patients. However, there have rarely been any published studies on how the amount of tumor in the positive prostate biopsy affects the predictive power of these imaging based assays. Recently we have proposed a new algorithmic framework for survival analysis employing semi-supervised transductive regression. This approach has improved the predictive power of biopsy based prostate cancer prognostic models. In this paper, we explore how different amounts of tumor in the prostate biopsy affect the accuracy of imaging based prognostic models employing this framework. We show that the framework improves accuracy even with diminishing amounts of tumor, thereby enabling more accurate treatment decisions.

Predicting and replacing the pathological Gleason grade with automated gland ring morphometric features from immunofluorescent prostate cancer images

The Gleason grade is the most common architectural and morphological assessment of prostate cancer severity and prognosis. There have been numerous algorithms developed to approximate and duplicate the Gleason scoring system, mostly developed in standard H&E brightfield microscopy. Immunofluorescence (IF) image analysis of tissue pathology has recently been proven to be robust in developing prognostic assessments of disease, particularly in prostate cancer. We leverage a method of segmenting gland rings in IF images for predicting the pathological Gleason, both the clinical and the image specific grades, which may not necessarily be the same. We combine these measures with nuclear specific characteristics. In 324 images from 324 patients, our individual features correlate well univariately with the Gleason grades and in a multivariate setting have an accuracy of 85% in predicting the Gleason grade. Additionally, these features correlate strongly with clinical progression outcomes [concordance index (CI) of 0.89], significantly outperforming the clinical Gleason grades (CI of 0.78). Finally, in multivariate models for multiple prostate cancer progression endpoints, replacing the Gleason with these features results in equivalent or improved performances. This work presents the first assessment of morphological gland unit features from IF images for predicting the Gleason grade, and even replacing it in prostate cancer prognostics.

Ornithine Decarboxylase Is Sufficient for Prostate Tumorigenesis via Androgen Receptor Signaling

Increased polyamine synthesis is known to play an important role in prostate cancer. We aimed to explore its functional significance in prostate tumor initiation and its link to androgen receptor (AR) signaling. For this purpose, we generated a new cell line derived from normal epithelial prostate cells (RWPE-1) with overexpression of ornithine decarboxylase (ODC) and used it for in vitro and in vivo experiments. We then comprehensively analyzed the expression of the main metabolic enzymes of the polyamine pathway and spermine abundance in 120 well-characterized cases of human prostate cancer and high-grade prostate intraepithelial neoplasia (HGPIN). Herein, we show that the ODC-overexpressing prostate cells underwent malignant transformation, revealing that ODC is sufficient for de novo tumor initiation in 94% of injected mice. This oncogenic capacity was acquired through alteration of critical signaling networks, including AR, EIF2, and mTOR/MAPK. RNA silencing experiments revealed the link between AR signaling and polyamine metabolism. Human prostate cancers consistently demonstrated up-regulation of the main polyamine enzymes analyzed (ODC, polyamine oxidase, and spermine synthase) and reduction of spermine. This phenotype was also dominant in HGPIN, rendering it a new biomarker of malignant transformation. In summary, we report that ODC plays a key role in prostate tumorigenesis and that the polyamine pathway is altered as early as HGPIN.

Natural Killer (NK) Cells’ Response to Epstein - Barr virus Infections and its Influence on the Risk of Developing Post-transplant Lymphoproliferative Disease (PTLD) after Allogeneic Hematopoietic Cell Transplantation: Effect of Donor Killer Ig-like Receptor Genes and Motifs Copy Numbers

BACKGROUND

Uncontrolled reactivation of Epstein-Barr virus (EBV) leading to post-transplant lymphoproliferative disorder (PTLD) is one of the major complications after T-cell depleted HCT. Recovering within weeks after HCT, natural killer (NK) cells are deemed important in the immunopathogenesis of EBV complications. Their role however remains elusive. NK cell responses are regulated by a series of activating and inhibitory cell surface receptors, central to which are the Killer Ig-like Receptors (KIR). Here we hypothesized and tested whether diverse NK cell receptor repertoires can titrate NK cell functional responses to EBV and can potentially modify the risk of developing PTLD.

METHODS

KIR genotypes, centromeric and telomeric motifs and their variants were determined for 356 allo-HCT donors through next generation sequencing of KIR locus. PBMNCs from KIR typed healthy volunteers were co-cultured with EBV-transformed cells and degranulation and IFNγ producing NK cells were enumerated using multi-parameter flow cytometry. Effect of donor KIR profile on PTLD was tested using competing risks regression statistics. Segregation of NK cell response to EBV across various KIR repertoires was tested by Mann-Whitney U statistics

RESULTS

At least one copy of Donor tA01 motifs was required for a strong protection against PTLD (p=0.0001, SHR=0.17). The number of EBV induced NK cells increased with increasing tA01 motifs. There was no influence of recipients’ KIR repertoire on the risk of developing PTLD.

CONCLUSIONS

KIR-regulated NK cells have a profound effect on the risk of PTLD. KIR gene profile based identification of HCT recipients at high risk of PTLD will enable closer monitoring of EBV DNAemia and facilitate prompt therapy.

Advanced tissue-based image analysis techniques integrated with biomarker-morphometric multiplex immunofluorescence to provide prostate cancer risk stratification models post-surgery

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Background: We have previously validated the importance of utilizing the intact tissue section and quantitative biomarker strategies for developing prognostic prostate cancer outcome models. We sought to further expand upon these constructs by applying next-gen advanced image analysis tools using multiplex immunofluorescence (IF) integrated with clinical variables on an independent cohort. Methods: Utilizing a 686 patient radical prostatectomy tissue microarray population with median 8 years follow-up from Roswell Park Cancer Institute, NY, we selected an initial subset of 98 patients to construct a training model; applying multiplex immunofluorescence with CK-18 (epithelial cells), CK 5/6 (basal cells), androgen receptor (AR), Ki67, AMACR and DAPI (nuclear marker). Images were captured with an Nikon i90 microscope equipped with a CRI multiplex camera, a Bayesian probabilistic approach was used to derive features that reflect tumor grade and co-locate - quantify IF biomarker expression within various glandular sub-types. Multivariate models were constructed to predict disease progression (i.e., clinical failure (CF) = PSA rise post-adjuvant therapy, or metastasis, or death) with c-index (CI) to estimate performance. Results: A 98 patient with the following clinical features: mean PSA 6.6 ng/mL, prostatectomy Gleason score, PGS 6, 34%; >/=PGS 7, 55%; LN+ 2%, +SM 19%; + ECE 49% ; + SVI 3%. CFevent rate 13%. Two models (i.e., +/- LN status) employing 47 features with 7 clinical variables (e.g., PSA and Gleason) had comparable outcomes, CI 0.84. The number one feature selected in both models was an imaging feature reflecting prostate cancer gland architecture and differentiation. Combined AR levels with gland phenotype and CK-18 composition characterized a relevant phenotype dependent upon feature inclusion in the model generated. Conclusions: We have established the importance of utilizing the intact tissue section when developing accurate prognostic prostate cancer models. Additional studies with expanded training and test patient cohorts are underway to confirm and validate these initial findings.

Abstract B04: Epithelial nuclear androgen receptor (AR) in radical prostatectomy samples as assessed by quantitative immunofluorescence is differentially expressed in African American versus Caucasian cases

Introduction: Numerous biomarkers are being evaluated as potential predictors of prostate cancer (PCa) recurrence after definitive surgical treatment with radical prostatectomy (RP). In particular, there is a significant literature on the importance of androgen receptor (AR) protein expression in predicting the aggressiveness of PCa as well as the probability of response to secondary therapeutic interventions (e.g. androgen deprivation therapy. The AR axis has been a primary target for researchers seeking treatment options for patients whose prostate cancer is not cured by surgery alone. By utilizing quantitative immunofluorescence (IF) multiplexed biomarkers assessd via spectral imaging, we evaluated whether AR expression is deferentially expressed by race.

Methods: We performed multiplex immunoflorescence immunohistochemistry on tissue microarrays (TMA) made from representative cores of tumor tissue from formalin-fixed, paraffin-embedded prostatectomy samples from cases treated for PCa by RP at the Henry Ford Health System between 2001 and 2005. There were 400 stained cores sampled from 149 African American (AA) cases and 453 cores from 195 Caucasian American (CM) cases. The samples were stained by a multiplex IF assay which contained the nuclear marker DAPI, along with AR and CK18. The co-localization of DAPI, CK18 and AR permitted quantitative analysis of AR expression in only the epithelial nuclei, a known cellular compartment of prognostic expression. Differences in expression were evaluated using the Wilcoxon rank sum test. The association between race and AR expression level was adjusted for potential confounding covariates using non-parametric generalized additive models.

Results: There was a statistically significant difference in the expression of AR signal in epithelial nuclei between Caucasian men and African American men, p-value = 0.03. The association between Race and AR remained statistically significant (p=0.02) even after adjusting for established clinical risk factors of PCa (age, grade, stage and PSA). It is also noteworthy that there were no statistically significant differences in age, grade, stage or PSA when comparing Caucasian and African American men in our dataset.

Conclusions: AR levels in RP epithelial nuclei have previously been found to be a useful tool in guiding therapeutic response for men who have failed surgical therapy for their prostate cancer. However, our results suggest that even with other clinical risk factors being equal, such molecular metrics may be different across racial subgroups of patients. It is possible that expression of these molecular features may be affected by external exposures, or genetic factors which differ by race, but are not necessarily related to the underlying disease mechanisms we seek to measure. Additional research into such differences is necessary as the African American community would benefit from the development of molecular diagnostic assays specifically tailored to this population. Current practices in biomarker discovery rarely address the possibility of racial variation, thereby leading to a potentially inaccurate or incorrect assessment of disease severity and consequent therapy for African American PCa patients.

Citation Format: Russell Bailey McBride, Faisal M. Khan, Benjamin A. Rybicki, Russell Cordon-Cardo. Epithelial nuclear androgen receptor (AR) in radical prostatectomy samples as assessed by quantitative immunofluorescence is differentially expressed in African American versus Caucasian cases. [abstract]. In: Proceedings of the Seventh AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 9-12, 2014; San Antonio, TX. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2015;24(10 Suppl):Abstract nr B04.

Low Counts of B Cells, Natural Killer Cells, Monocytes, Dendritic Cells, Basophils, and Eosinophils are Associated with Postengraftment Infections after Allogeneic Hematopoietic Cell Transplantation

Hematopoietic cell transplant (HCT) recipients are immunocompromised and thus predisposed to infections. We set out to determine the deficiency of which immune cell subset(s) may predispose to postengraftment infections. We determined day 28, 56, 84, and 180 blood counts of multiple immune cell subsets in 219 allogeneic transplant recipients conditioned with busulfan, fludarabine, and Thymoglobulin. Deficiency of a subset was considered to be associated with infections if the low subset count was significantly associated with subsequent high infection rate per multivariate analysis in both discovery and validation cohorts. Low counts of monocytes (total and inflammatory) and basophils, and low IgA levels were associated with viral infections. Low plasmacytoid dendritic cell (PDC) counts were associated with bacterial infections. Low inflammatory monocyte counts were associated with fungal infections. Low counts of total and naive B cells, total and CD56(high) natural killer (NK) cells, total and inflammatory monocytes, myeloid dendritic cells (MDCs), PDCs, basophils and eosinophils, and low levels of IgA were associated with any infections (due to any pathogen or presumed). In conclusion, deficiencies of B cells, NK cells, monocytes, MDCs, PDCs, basophils, eosinophils, and/or IgA plasma cells appear to predispose to postengraftment infections.

Prostate cancer prognosis via integrative and co-localized glandular morphometry and immunofluorescent protein biomarker expression

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Background: Quantitative image analysis of both the prostate needle biopsy (PNB) and the radical prostatectomy sample (RPS) have proven to be robust and predictive for prostate cancer (PCa) prognosis. While metrics assessing morphology and protein biomarker expression separately have been published in prognostic risk prediction models, we sought to determine the performance of novel approaches which combine protein biomarker expression with the morphometry of the gland wherein they express. In order to assess robustness, we evaluated these metrics in both PNB and RPS cohorts. Methods: Novel quantitative biometric features were derived from computerized analysis of morphology and immunofluorescent (IF) biomarker expression in PCa images. A Bayesian probabilistic approach to co-locate and quantify IF biomarker expression within various glandular sub-types was developed. This permitted differentiable analysis of PCa biomarkers such as androgen receptor (AR) in high and low Gleason grade glands of the same patient. Performance in predicting significant clinical disease progression (including metastasis and death-of-disease) was assessed via the concordance index (CI). Performance was evaluated independently in a cohort of 326 PNB samples (median 8-year follow up) and a cohort of 373 RPS (median 5-year follow up). Results: In a univariate analysis, previously published glandular morphology features had a CI of 0.68 (PNB) and 0.76 (RPS). Quantitative AR had a CI of 0.67 (PB) and 0.72 (RPS). Novel metrics of integrative co-localization resulted in a significant increase in prognostic accuracy; CIs of 0.72 (PNB) and 0.83 (RPS). These features separately assessed AR expression depending on the multiple glandular sub-types within the tumor sample. Conclusions: Integrating quantitative image analysis of morphology and IF biomarker expression in the PNB and RPS outperformed previous quantitative metrics. Such robust and reproducible metrics may prove beneficial in improving risk stratification models for future treatment decision making.

A quantitative image analysis model of prostate biopsies for predicting clinical risk in men enrolled in an active surveillance program

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Background: Quantitative image analysis of the prostate needle biopsy (PNB) has proven to be a robust and predictive platform for prostate cancer (PCa) prognosis. We sought to determine the performance of quantitative metrics in identifying which patients enrolled in an active surveillance (AS) program are most likely to present with significant clinical risk, including subsequent biopsy Gleason grade (GG) upgrading and/or a short (less than 24 month) prostate-specific antigen (PSA) doubling time (PSADT). Methods: One hundred sixty two AS patients (median age 70, 94% cT1-T2a, 85% <=GS6, median PSA 5.9 ng/mL) with overall 8 year median follow up and available diagnostic PNB specimens were analyzed. Computerized image analysis derived quantitative biometric features representing PCa morphology and immunofluorescent (IF) biomarkers from the PNB. Multivariate models predicting either GG upgrading on a subsequent PNB or a PSADT less than 24 months were evaluated. The AUC/concordance index (CI), sensitivity, specificity and hazard ratio (HR) were used to assess performance. Results: Univariate distribution of selective features, notably expression levels of AR and Ki67, were reflective of a low risk cohort.A multivariate model with three quantitative imaging metrics was trained with a CI of 0.77. Men at high risk within 24 months of the PNB were identified with 80% sensitivity and 73% specificity, HR of 5.7. The most important feature measured the relative proportion of tumor epithelial nuclei that were both Androgen Receptor and alpha-methylacyl-CoA racemase positive. The other two features were morphological assessments of epithelial cellular area compared to luminal area. Of note, clinical features such as age, GG and PSA were not selected in competition with the imaging metrics. Conclusions: Quantitative image analysis of morphology and IF biomarker expression in the PNB outperformed standard clinical features in a multivariate model to accurately predict which AS patients are at risk for Gleason upgrading and/or a shortened PSADT. Identifying such patients may prove beneficial in the primary treatment decision process.

Immune cell subset counts associated with graft-versus-host disease

Graft-versus-host disease (GVHD) is a major transplantation complication. The purpose of this study was to measure immune cell subsets by flow cytometry early after transplantation (before median day of GVHD onset) to identify subsets that may play a role in GVHD pathogenesis. We also measured the subsets later after transplantation to determine which subsets may be influenced by GVHD or its treatment. We studied 219 patients. We found that acute GVHD (aGVHD) was preceded by high counts of CD4 T cells and CD8 T cells. It was followed by low counts of total and naive B cells, total and cytolytic NK cells, and myeloid and plasmacytoid dendritic cells. Chronic GVHD (cGVHD) was preceded by low counts of memory B cells. In conclusion, both CD4 and CD8 T cells appear to play a role in the pathogenesis of aGVHD. Generation of B cells, NK cells, and dendritic cells may be hampered by aGVHD and/or its treatment. Memory B cells may inhibit the development of cGVHD.

Gland ring morphometry for prostate cancer prognosis in multispectral immunofluorescence images

Morphometric features characterizing the fusion and fragmentation of the glandular architecture of advanced prostate cancer have not previously been based upon the automated segmentation of discrete gland rings, due in part to the difficulty of extracting these structures from the H&E stained tissues. We present a novel approach for segmenting gland rings in multi-spectral immunofluorescence (IF) images and demonstrate the utility of the resultant features in predicting cancer recurrence in a cohort of 1956 images of prostate biopsies and prostatectomies from 679 patients. The proposed approach is evaluated for prediction of actual clinical outcomes of interest to physicians in comparison with previously published gland-unit features, yielding a concordance index (CI) of 0.67. This compares favorably to the CI of 0.66 obtained using a semi-automated segmentation of the corresponding H&E images from the same patients. This work presents the first algorithms for segmentation of gland rings lacking a central lumen, and for separation of touching epithelial units, and introduces new gland adjacency features for predicting prostate cancer clinical progression across both biopsy and prostatectomy images.

Factors responsible for increased percent recirculation in arterio-venous fistula among the haemodialysis patients

Recirculation is an important issue in haemodialysis (HD) patients as increased percent recirculation causes decreased dialysis delivery of the patients. The purpose of the study was to determine the amount and factors of recirculation in those patients. The study was a cross sectional one carried in the Department of Nephrology, Dhaka Medical College and Hospital during October 2010 to September 2011. A total of 118 end stage renal disease patients with arterio-venous fistula who were on HD for more than 3 months were purposively selected. The degree of recirculation was measured with urea based two needle technique method. For each patient distances between arterial and venous and distances of needles from fistula and its directions were recorded. Echocardiography and A-V fistula Colour Doppler Ultrasound were also performed. The mean A-V fistula recirculation was 8.1 +/- 5.5% with a range 0-66%. The most common factors were close proximity and improper arterial and venous needles placement. No difference was observed between diabetic and non diabetic also between hypertensive and normotensive. A-V fistula recirculation is common occurrence in HD patients and the most common factors of recirculation are misplacement and close proximity of needles therefore emphasis should be given on education and training of HD staffs.