Development of a Precision Medicine Workflow in Hematological Cancers, Aalborg University Hospital, Denmark

Within recent years, many precision cancer medicine initiatives have been developed. Most of these have focused on solid cancers, while the potential of precision medicine for patients with hematological malignancies, especially in the relapse situation, are less elucidated. Here, we present a demographic unbiased and observational prospective study at Aalborg University Hospital Denmark, referral site for 10% of the Danish population. We developed a hematological precision medicine workflow based on sequencing analysis of whole exome tumor DNA and RNA. All steps involved are outlined in detail, illustrating how the developed workflow can provide relevant molecular information to multidisciplinary teams. A group of 174 hematological patients with progressive disease or relapse was included in a non-interventional and population-based study, of which 92 patient samples were sequenced. Based on analysis of small nucleotide variants, copy number variants, and fusion transcripts, we found variants with potential and strong clinical relevance in 62% and 9.5% of the patients, respectively. The most frequently mutated genes in individual disease entities were in concordance with previous studies. We did not find tumor mutational burden or micro satellite instability to be informative in our hematologic patient cohort

Nationwide Survival Benefit after Implementation of First-Line Immunotherapy for Patients with Advanced NSCLC—Real World Efficacy

SIMPLE SUMMARY: The expected change in overall survival (OS) in patients with advanced non-small cell lung cancer (NSCLC) after the clinical implementation of immune checkpoint inhibitor therapy (ICI) has not been substantially investigated in large real-world cohorts outside randomized controlled trials (RCTs). In this nationwide study, we compared OS before and after the implementation of ICI and found that 3-year OS tripled from 6% to 18%. Patients receiving ICI had a lower OS than demonstrated in RCTs, except for patients with performance status (PS) 0. More than a fifth of the patients progressed early within the first six ICI cycles. Adverse prognostic factors were PS ≥ 1 and metastases to the bone and liver. ABSTRACT: Background The selection of patients with non-small cell lung cancer (NSCLC) for immune checkpoint inhibitor (ICI) treatment remains challenging. This real-world study aimed to compare the overall survival (OS) before and after the implementation of ICIs, to identify OS prognostic factors, and to assess treatment data in first-line (1L) ICI-treated patients without epidermal growth factor receptor mutation or anaplastic lymphoma kinase translocation. Methods Data from the Danish NSCLC population initiated with 1L palliative antineoplastic treatment from 1 January 2013 to 1 October 2018, were extracted from the Danish Lung Cancer Registry (DLCR). Long-term survival and median OS pre- and post-approval of 1L ICI were compared. From electronic health records, additional clinical and treatment data were obtained for ICI-treated patients from 1 March 2017 to 1 October 2018. Results The OS was significantly improved in the DLCR post-approval cohort (n = 2055) compared to the pre-approval cohort (n = 1658). The 3-year OS rates were 18% (95% CI 15.6–20.0) and 6% (95% CI 5.1–7.4), respectively. On multivariable Cox regression, bone (HR = 1.63) and liver metastases (HR = 1.47), performance status (PS) 1 (HR = 1.86), and PS ≥ 2 (HR = 2.19) were significantly associated with poor OS in ICI-treated patients. Conclusion OS significantly improved in patients with advanced NSCLC after ICI implementation in Denmark. In ICI-treated patients, PS ≥ 1, and bone and liver metastases were associated with a worse prognosis

A multiple myeloma classification system that associates normal B-cell subset phenotypes with prognosis.

Despite the recent progress in treatment of multiple myeloma (MM), it is still an incurable malignant disease, and we are therefore in need of new risk stratification tools that can help us to understand the disease and optimize therapy. Here we propose a new subtyping of myeloma plasma cells (PCs) from diagnostic samples, assigned by normal B-cell subset associated gene signatures (BAGS). For this purpose, we combined fluorescence-activated cell sorting and gene expression profiles from normal bone marrow (BM) Pre-BI, Pre-BII, immature, naïve, memory, and PC subsets to generate BAGS for assignment of normal BM subtypes in diagnostic samples. The impact of the subtypes was analyzed in 8 available data sets from 1772 patients' myeloma PC samples. The resulting tumor assignments in available clinical data sets exhibited similar BAGS subtype frequencies in 4 cohorts from de novo MM patients across 1296 individual cases. The BAGS subtypes were significantly associated with progression-free and overall survival in a meta-analysis of 916 patients from 3 prospective clinical trials. The major impact was observed within the Pre-BII and memory subtypes, which had a significantly inferior prognosis compared with other subtypes. A multiple Cox proportional hazard analysis documented that BAGS subtypes added significant, independent prognostic information to the translocations and cyclin D classification. BAGS subtype analysis of patient cases identified transcriptional differences, including a number of differentially spliced genes. We identified subtype differences in myeloma at diagnosis, with prognostic impact and predictive potential, supporting an acquired B-cell trait and phenotypic plasticity as a pathogenetic hallmark of MM

Extracting Systemic Anticancer Treatment Lines from the Danish National Patient Registry for Solid Tumour Patients Treated in the North Denmark Region Between 2009 and 2019

Charles Vesteghem,1,2 Martin Bøgsted,1,2 Deirdre Cronin-Fenton,3 Laurids Østergaard Poulsen2,4 1Center for Clinical Data Science, Aalborg University and Aalborg University Hospital, Aalborg, Denmark; 2Clinical Cancer Research Centre, Aalborg University Hospital, Aalborg, Denmark; 3Department of Clinical Epidemiology, Department of Clinical Medicine, Aarhus University and Aarhus University Hospital, Aarhus, Denmark; 4Department of Oncology, Aalborg University Hospital, Aalborg, DenmarkCorrespondence: Charles Vesteghem, Center for Clinical Data Science, Aalborg University and Aalborg University Hospital, Selma Lagerløfs Vej 249, Gistrup, 9260, Denmark, Email [email protected]: Reconstructing patient treatment trajectories is important to generate real-world evidence for epidemiological studies. The Danish National Patient Registry (DNPR) contains information about drug prescriptions and could therefore be used to reconstruct treatment trajectories. We aimed to evaluate and enhance two existing methods to reconstruct systemic anticancer treatment trajectories.Methods: This study was based on data from 8738 consecutive patients with solid tumors treated in the North Denmark Region between 2009 and 2019. Two approaches found in the literature as well as two new approaches were applied to the DNPR data. All methods relied on time intervals between two consecutive drug administrations to determine if they belonged to the same treatment line. MedOnc, a local dataset from the Department of Oncology, Aalborg University Hospital was used as a reference. To evaluate the performance of each method, F1-scores were calculated after matching the lines identified in both datasets. We used three different matching strategies: stringent matching, loose matching, and matching based on line numbers, controlling for overfitting.Results: Overall, the two new approaches outperformed the simpler and best performing of the two existing methods, with F1-scores of 0.47 and 0.45 vs 0.44 for stringent matching and 0.84 and 0.83 vs 0.82 for loose matching. Nevertheless, only one of the new methods outperformed the existing simpler method when matching on the number of lines (0.73 vs 0.72). Large differences were seen by cancer site, especially for the stringent and line number matchings. Performances were relatively stable by calendar year.Conclusion: The high F1-scores for the new methods confirm that they should be generally preferred to reconstruct systemic anticancer treatment trajectories using the DNPR.Keywords: anticancer treatment, epidemiology, patient trajectory, Danish National Patient Register, treatment lin

Nationwide Survival Benefit after Implementation of First-Line Immunotherapy for Patients with Advanced NSCLC—Real World Efficacy

Background The selection of patients with non-small cell lung cancer (NSCLC) for immune checkpoint inhibitor (ICI) treatment remains challenging. This real-world study aimed to compare the overall survival (OS) before and after the implementation of ICIs, to identify OS prognostic factors, and to assess treatment data in first-line (1L) ICI-treated patients without epidermal growth factor receptor mutation or anaplastic lymphoma kinase translocation. Methods Data from the Danish NSCLC population initiated with 1L palliative antineoplastic treatment from 1 January 2013 to 1 October 2018, were extracted from the Danish Lung Cancer Registry (DLCR). Long-term survival and median OS pre- and post-approval of 1L ICI were compared. From electronic health records, additional clinical and treatment data were obtained for ICI-treated patients from 1 March 2017 to 1 October 2018. Results The OS was significantly improved in the DLCR post-approval cohort (n = 2055) compared to the pre-approval cohort (n = 1658). The 3-year OS rates were 18% (95% CI 15.6–20.0) and 6% (95% CI 5.1–7.4), respectively. On multivariable Cox regression, bone (HR = 1.63) and liver metastases (HR = 1.47), performance status (PS) 1 (HR = 1.86), and PS ≥ 2 (HR = 2.19) were significantly associated with poor OS in ICI-treated patients. Conclusion OS significantly improved in patients with advanced NSCLC after ICI implementation in Denmark. In ICI-treated patients, PS ≥ 1, and bone and liver metastases were associated with a worse prognosis

Supplementary Table_S1: Direct costs of antineoplastic and supportive treatment for progressive multiple myeloma in a tax-based health system.xlsx

Supplementary Figure 1. Direct costs of antineoplastic and supportive treatment for progressive multiple myeloma in a tax-based health system This table contains the Anatomical Therapeutic Chemical (ATC) codes for all drugs included in this analysis