No abstract

Summary Published studies on the epidemiology of amyloidosis have relied on death certificate data for case ascertainment. We estimated the incidence and mortality burden of amyloidosis among residents of the Australian state, Queensland, aged ≥20 years for the years 1999–2013 based on case ascertainment from histopathology reports. Information systems for participating laboratories were scrutinised to identify histopathology reports that documented a diagnosis of amyloidosis. Case mortality status was determined via linkage to the National Death Index. A total of 447 cases of amyloidosis were identified, with a median age at diagnosis of 66 years. A plasma cell dyscrasia was identified in 72% of patients who had paraprotein studies performed. The estimated incidence for Queenslanders aged ≥20 years was 12·1 cases per million person years. The median survival was 2·45 years. Age at diagnosis, presence of a paraprotein, earlier year of diagnosis, and inner regional location of residence (compared with residence in a major city) were independently associated with reduced survival. Our data confirms previously reported incidence data for amyloidosis of approximately 10 cases per million patient years and indicates that survival for Queensland patients with amyloidosis is improving, though it remains poor for the elderly and patients with AL amyloidosis.

Background Lymphoma is a malignancy of lymphocytes and lymphoid tissues comprising a heterogeneous group of diseases, with up to 80 entities now described. Lymphoma is the 6th most common cancer in Australia, affecting patients of all ages, with rising incidence rates. With the proliferation of efficacious novel agents, therapeutic strategies are increasingly diverse and survival is improving. There is a clear need for contemporary robust and detailed data on diagnostic, investigational and management strategies for this disease in Australia, New Zealand and worldwide, to inform and benchmark local and international standards of care. Clinical quality registries can provide these data, and support development of strategies to address variations in management, including serving as platforms for clinical trials and research. The Lymphoma and Related Diseases Registry (LaRDR) was developed to capture details of patient demographics, disease characteristics, and management throughout their disease course and therapy and to develop outcome benchmarks nationally and internationally for lymphoma. This report describes the aims, development and implementation of the LaRDR, as well as challenges addressed in the process.Methods The LaRDR was established in 2016 as a multicentre, collaborative project at sites across Australia with a secure online database which collects prospective data on patients with a new diagnosis of lymphoma or chronic lymphocytic leukaemia (CLL). LaRDR development required multidisciplinary participation including specialist haematology, information technology, and biostatistical support, as well as secure funding. Here we describe the database development, data entry, ethics approval process, registry governance and support for participating sites and the coordinating centre.Results To date more than 4,700 patients have been enrolled from 27 sites. Multiple challenges arose during the development, which we describe, along with approaches used to overcome them. Several confirmed international collaborations are now in place, and the registry is providing valuable data for clinicians, researchers, industry and government, including through presentations of results at major national and international conferences.Conclusion Challenges in establishing the LaRDR have been successfully overcome and the registry is now a valuable resource for lymphoma clinicians, researchers, health economists and others in Australia and globally.

Results: All 45 pts received at least one dose of study drug. The median age was 69 years; 93% were >60 years, 33% ECOG >1, 82%Stage III/IV, and 78% IPI 3-5. Of the 29 pts with cell of origin (COO) status by digital gene expression, 11 (38%) were ABC, 14 (48%) were GCB, while 4 (14%) were unclassified. Forty patients completed 6 or 8 cycles (23 and 17 pts respectively). All pts experienced at least one AE. Grade (Gr) 3/4 AEs occurred in 58%, and one pt experienced a Gr 5 atrial fibrillation. Gr 3/4 neutropenia and febrile neutropenia (FN) occurred in 27% and 11%. Serious adverse events (SAEs) were reported in 17 pts (38%) including 3 FN, and 2 each of neutropenia, pneumonia, pulmonary embolism and influenza A.Peripheral neuropathy (PN) occurred in 18 (40%) patients. Among these pts with PN, 12 were Gr 1, 4 were Gr 2, and 2 were Gr 3. All Gr 2/3 PN attributed to pola occurred at C5 or later.Four pts discontinued pola early for the following reasons: Gr 5 atrial fibrillation (after C2, not attributed to pola by investigator), E. coli UTI (C5), worsening essential tremor (C3), PN (C7). During treatment, 6 pts had dose reductions in pola and 1 pt had cyclophosphamide and doxorubicin dose reductions.ORR by PET at EOT was 91%; 78% had a CR and 13% PR. 3 pts progressed and 1 was unevaluable. In the COO determined population, CR was 91% in ABC and 86% in GCB pts. At the data cutoff of November 4, 2016 with a median study duration of 9.5 months, (range 1.3-28 months), only 1 pt had a disease progression in follow up.Conclusions: Pola at 1.8 mg/kg in combination with R-CHP in 1 L DLBCL has an acceptable safety profile and produced promising response rates at the end of treatment. The majority of the patients in this trial represented a poor prognosis group by age and IPI. In this context, treatment response to this regimen may warrant further exploration.

Technologies, Seattle, WA) as a "locked" biomarker as previously described (Scott et al., J Clin Oncol 2013; 31:692-700). The threshold previously described was trained on overall survival (OS) after ABVD.The performance of the assay at predicting PET2 and OS in RATHL was tested using this threshold, then receiver operating characteristic (ROC) analysis was used to assess if a better threshold could be found for our cohort.Results: 284 patients were analysable as GEP failed in 31 patients.Comparing baseline demographics, the high risk GEP group had an excess of elderly, male and higher disease stage pts. The GEP score was not able to predict PET2 positivity (PET2+); 16 (12.1%) high risk pts and 26 (17.1%) low risk pts were PET2+ (12.5% and 18.3% in the stage III-IV group). Performing ROC analysis using the score as a continuous variable did not suggest a different cut off would perform better (area under the curve: 43.8%). GEP risk was associated with poorer OS in univariable analysis (3 year OS 98% vs 93% for low and high risk, respectively) but this lost significance when adjusted for other baseline factors. The classifier was not prognostic for PFS in any group in RATHL (whole population, PET2-or PET2+). Conclusions:The GEP based model was not predictive of PET2 response and is not a suitable method for determining escalation of treatment. A higher proportion of patients were assigned to the high risk group in the RATHL trial and OS was higher compared with the original intergroup study, however based on these results, a refined GEP based model with validation across other platforms is required for this modality to be used as a baseline predictor of outcome in CHL. Keywords: gene expression profile (GEP); Hodgkin lymphoma (HL);positron emission tomography (PET). demonstrates that the assay is not predictive of PET2 positivity. Furthermore, the assay was not predictive of PFS, with a 2-year PFS of 80% and 84% in the low-and high-risk groups, respectively (log rank P = 0.65). There were not sufficient events to test the prognostic power of the assay for OS. THE 23-GENE GENE EXPRESSION-BASED ASSAY DOES NOT PREDICT INTERIM PET SCAN RESULTS AFTER ABVD IN Conclusions:The 23-gene assay, trained on the endpoint of OS, was not predictive of PET2 results. Furthermore, it was not predictive of PFS in this trial of response-adapted treatment. These results provide strong evidence that this assay should not be used for risk stratification where response-adapted therapy is utilized.