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Type 2 diabetes mellitus (T2DM) can be multifactorial where both genetics and environmental factors play a role. We aimed to investigate the use of polygenic risk scores (PRS) in the prediction of pre-transplant T2DM and post-transplant diabetes mellitus (PTDM) among solid organ transplant (SOT) patients. Using non-genetic risk scores alone; and the combination with PRS, separate logistic regression models were built and compared using receiver operator curves. Patients were assessed pre-transplant and in three post-transplant periods: 0-45, 46-365 and >365 days. A higher PRS was significantly associated with increased odds of pre-transplant T2DM. However, no improvement was observed for pre-transplant T2DM prediction when comparing PRS combined with non-genetic risk scores to using non-genetic risk scores alone. This was also true for predictions of PTDM in all three post-transplant periods. This study demonstrated that polygenic risk was only associated with the risk of T2DM among SOT recipients prior to transplant and not for PTDM. Combining PRS with a clinical model of non-genetic risk scores did not significantly improve the predictive ability, indicating its limited clinical utility in identifying patients at high risk for T2DM before transplantation, suggesting that non-genetic or different genetic factors may contribute to PTDM., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 dos Santos, Leung, Thorball, Ledergerber, Fellay, MacPherson, Hornum, Terrones-Campos, Rasmussen, Gustafsson, Perch, Sørensen, Ekenberg, Lundgren, Feldt‐Rasmussen and Reekie.)

Post-transplant diabetes mellitus (PTDM) is associated with a higher risk of adverse outcomes. We aimed to describe the proportion of patients with diabetes prior to solid organ transplantation (SOT) and post-transplant diabetes mellitus (PTDM) in three time periods (early-likely PTDM: 0-45 days; 46-365 days and >365 days) post-transplant and to estimate possible risk factors associated with PTDM in each time-period. Additionally, we compared the risk of death and causes of death in patients with diabetes prior to transplant, PTDM, and non-diabetes patients. A total of 959 SOT recipients (heart, lung, liver, and kidney) transplanted at University Hospital of Copenhagen between 2010 and 2015 were included. The highest PTDM incidence was observed at 46-365 days after transplant in all SOT recipients. Age and the Charlson Comorbidity Index (CCI Score) in all time periods were the two most important risk factors for PTDM. Compared to non-diabetes patients, SOT recipients with pre-transplant diabetes and PTDM patients had a higher risk of all-cause mortality death (aHR: 1.77, 95% CI: 1.16-2.69 and aHR: 1.89, 95% CI: 1.17-3.06 respectively). Pre-transplant diabetes and PTDM patients had a higher risk of death due to cardiovascular diseases and cancer, respectively, when compared to non-diabetes patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Dos Santos, Hornum, Terrones-Campos, Crone, Wareham, Soeborg, Rasmussen, Gustafsson, Perch, Soerensen, Lundgren, Feldt-Rasmussen and Reekie.)

Purpose: The incidence, etiology, and association of infections with radiation therapy (RT)-induced lymphopenia in patients with solid tumors is not well elucidated., Methods and Materials: We identified possible, probable, and definite infections caused by bacteria, fungi, and viruses, combining data on medication, microbiology, and diagnoses. Definite infections had either a diagnosis or a positive microbiological isolation. We analyzed the incidence and adjusted incidence-rate ratio of infections in the year after the start of RT among patients who received RT plus chemotherapy and RT monotherapy, by type of infection and according to the degree of RT-induced lymphopenia., Results: A total of 4450 of 6334 (70.3%) patients experienced 11264 infections overall; 1424 (22.5%) patients developed 2104 definite infections in the first year after RT. Infections were more frequent among patients who received RT plus chemotherapy (2590 of 3469; incidence: 16.5 [95% confidence interval {CI}, 16.1-17.0], per 100 patient-years) compared with patients who received RT monotherapy (1860 of 2865; incidence: 12.7 [95% CI, 12.3-13.2]). The incidence of infection was highest in the first 3 months overall (28.2 vs 18.0 in patients who received RT plus chemotherapy compared with those who received RT monotherapy) and for definite infections (4.7 vs 3.8). The proportion of specific bacterial infections were similar among patients who received RT plus chemotherapy versus those who received RT monotherapy. Urinary tract infections were the most frequent (51.2% vs 56.2%), followed by pneumonias (24.1% vs 22.4%). Viral and fungal infections were more frequent among patients who received RT plus chemotherapy, but they were uncommon. In multivariable analyses, patients who received RT plus chemotherapy with a lymphopenia grade of 1-2 or ≥3 versus no lymphopenia at end of RT had an increased risk of bacterial infections 0 to 3 months after RT (incidence rate ratio, 1.45 [95% CI, 1.06-1.97] and 1.71 [95% CI, 1.26-2.34], respectively). Limiting to definite bacterial infections, the incidence rate ratio for lymphopenia grade ≥3 versus no lymphopenia was 2.66 (95% CI, 1.40-5.03)., Conclusions: The incidence of bacterial infections 0 to 3 months after RT plus chemotherapy for solid tumors was high, especially among patients with RT-induced lymphopenia grade 1-2 and ≥3., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors.)

Purpose: Organ-at-risk contouring is still a bottleneck in radiotherapy, with many deep learning methods falling short of promised results when evaluated on clinical data. We investigate the accuracy and time-savings resulting from the use of an interactive-machine-learning method for an organ-at-risk contouring task., Methods: We implement an open-source interactive-machine-learning software application that facilitates corrective-annotation for deep-learning generated contours on X-ray CT images. A trained-physician contoured 933 hearts using our software by delineating the first image, starting model training, and then correcting the model predictions for all subsequent images. These corrections were added into the training data, which was used for continuously training the assisting model. From the 933 hearts, the same physician also contoured the first 10 and last 10 in Eclipse (Varian) to enable comparison in terms of accuracy and duration., Results: We find strong agreement with manual delineations, with a dice score of 0.95. The annotations created using corrective-annotation also take less time to create as more images are annotated, resulting in substantial time savings compared to manual methods. After 923 images had been delineated, hearts took 2 min and 2 s to delineate on average, which includes time to evaluate the initial model prediction and assign the needed corrections, compared to 7 min and 1 s when delineating manually., Conclusions: Our experiment demonstrates that interactive-machine-learning with corrective-annotation provides a fast and accessible way for non computer-scientists to train deep-learning models to segment their own structures of interest as part of routine clinical workflows., (© 2021 American Association of Physicists in Medicine.)

Purpose: To describe the kinetics of the peripheral blood components after radiotherapy, to examine radiation exposure vs. End-of-Radiation-Therapy (EoRT) counts and to associate the EoRT lymphocyte count with death and cancer treatment failure., Materials and Methods: Cohort study of patients who received curative intent radiotherapy for solid tumor diagnoses from 2009-2016 at Rigshospitalet, Copenhagen and had available 3D radiation exposure data. We illustrated peripheral blood count kinetics within 12 months before and after radiotherapy start and analyzed the impact of the irradiated body volume. We investigated overall survival and cancer treatment failure according to EoRT lymphopenia using Cox regression analyses., Results: We analyzed 4055 patients with both pre-treatment and EoRT platelet counts and 2318 patients who also had neutrophil and lymphocyte counts. Only the lymphocyte decline after radiotherapy start was clinically relevant and remained low one year after radiotherapy. The higher the volume of the body exposed to radiation, the lower the EoRT blood counts. Female gender (p < 0.001), number of fractions (p = 0.010), dose-volume (p < 0.001) and concomitant use of chemotherapy, particularly the platinum compounds (p < 0.001) were independently associated with a lower EoRT lymphocyte count. Patients with head and neck cancer had the lowest EoRT lymphocyte count. Patients with lymphopenia had a higher risk of death in the year after radiotherapy, compared with patients with no lymphopenia., Conclusion: Radiation schemes with fewer fractions and radiation techniques allowing reduction of the volume of the body exposed to radiation could be expected to better preserve patients' immune function., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Purpose: Lymphopenia has been associated with poor outcomes in patients with cancer. We sought to describe the lymphocyte kinetics in patients who received radiation therapy; to identify factors associated with the end-of-radiation-therapy (EoRT) lymphocyte count; and to determine the association of radiation therapy-induced lymphopenia with subsequent infection., Methods and Materials: Patients with solid malignant tumors treated at the Department of Oncology at Rigshospitalet, University of Copenhagen, Denmark, were included if they had received their first external beam radiation therapy with curative intent from January 2005 to December 2016 and had pretreatment and EoRT lymphocyte counts measured. Factors associated with the EoRT lymphocyte count were identified using regression analyses. The risk of subsequent infection was estimated using Cox proportional hazards regression., Results: We included 3920 patients. More patients had lymphopenia (<1000 cells/μL) at EoRT than at pretreatment (67.1% vs 14.9%; P < .001). Patients who received schemes with higher intensities (equivalent dose in 2-Gy fractions [EQD2] >65 Gy) in shorter time (<25 days) had a higher predicted EoRT lymphocyte count than patients who received schemes delivering EQD2 of 50 to 65 Gy in 25 to 45 days (1439 cells/μL, 95% confidence interval [1293-1585] vs 784 [754-814]). Radiation to multiple sites and concomitant chemotherapy use, particularly platinum compounds versus none, were associated with a lower EoRT lymphocyte count (698 [655-742] vs 852 [833-870]; and 612 [565-659] vs 937 [909-964], respectively). Patients with EoRT lymphopenia grade ≥3 (<500 cells/μL) had a higher risk of infection in the 3 months after radiation therapy (hazard ratio, 2.15 [95% confidence interval, 1.53-3.02]; P < .001), compared with patients with an EoRT lymphocyte count >1000 cells/μL., Conclusions: The lymphocyte count declined during radiation therapy. Short duration schemes (<25 days), despite high total radiation dose (EQD2 >65 Gy), were associated with a higher EoRT lymphocyte count, whereas radiation to multiple sites and concomitant chemotherapy were associated with a lower count. EoRT lymphopenia was associated with an increased risk of infection., (Copyright © 2019 Elsevier Inc. All rights reserved.)