6 results on '"Kamper, Peter"'
Search Results
2. Pulmonary diseases in patients with classical Hodgkin lymphoma relative to a matched background population: A Danish national cohort study.
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Vandtved, Julie Haugaard, Øvlisen, Andreas Kiesbye, Baech, Joachim, Weinrich, Ulla Møller, Severinsen, Marianne Tang, Maksten, Eva Futtrup, Jakobsen, Lasse Hjort, Glimelius, Ingrid, Kamper, Peter, Hutchings, Martin, Specht, Lena, Dahl‐Sørensen, Rasmus, Christensen, Jacob Haaber, and El‐Galaly, Tarec C.
- Subjects
OBSTRUCTIVE lung diseases ,INTERSTITIAL lung diseases ,PULMONARY fibrosis ,CHRONIC obstructive pulmonary disease ,LUNG diseases - Abstract
Summary: Late toxicities can impact survivorship in patients with classical Hodgkin lymphoma (cHL) with pulmonary toxicity after bleomycin‐containing chemotherapy being a concern. The incidence of pulmonary diseases was examined in this Danish population‐based study. A total of 1474 adult patients with cHL treated with ABVD (doxorubicin, bleomycin, vinblastine and dacarbazine) or BEACOPP (bleomycin, vincristine, etoposide, doxorubicin, cyclophosphamide, procarbazine and prednisone) between 2000 and 2018 were included along with 7370 age‐ and sex‐matched comparators from the background population. Median follow‐up was 8.6 years for the patients. Patients with cHL had increased risk of incident pulmonary diseases (HR 2.91 [95% CI 2.30–3.68]), with a 10‐year cumulative risk of 7.4% versus 2.9% for comparators. Excess risks were observed for interstitial lung diseases (HR 15.84 [95% CI 9.35–26.84]) and chronic obstructive pulmonary disease (HR 1.99 [95% CI 1.43–2.76]), with a 10‐year cumulative risk of 4.1% and 3.5% respectively for patients. No excess risk was observed for asthma (HR 0.82 [95% CI 0.43–1.56]). Risk factors for interstitial lung diseases were age ≥60 years, the presence of B‐symptoms and low albumin. These findings document a significant burden of pulmonary diseases among patients with cHL and emphasize the importance of diagnostic work‐up of pulmonary symptoms. [ABSTRACT FROM AUTHOR]
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- 2024
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3. Machine Learning–Based Survival Prediction Models for Progression-Free and Overall Survival in Advanced-Stage Hodgkin Lymphoma
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Rask Kragh Jørgensen, Rasmus, primary, Bergström, Fanny, additional, Eloranta, Sandra, additional, Tang Severinsen, Marianne, additional, Bjøro Smeland, Knut, additional, Fosså, Alexander, additional, Haaber Christensen, Jacob, additional, Hutchings, Martin, additional, Bo Dahl-Sørensen, Rasmus, additional, Kamper, Peter, additional, Glimelius, Ingrid, additional, E Smedby, Karin, additional, K Parsons, Susan, additional, Mae Rodday, Angie, additional, J Maurer, Matthew, additional, M Evens, Andrew, additional, C El-Galaly, Tarec, additional, and Hjort Jakobsen, Lasse, additional
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- 2024
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4. The Genetic Profile of Large B-Cell Lymphomas Presenting in the Ocular Adnexa
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Vest, Stine Dahl, primary, Eriksen, Patrick Rene Gerhard, additional, de Groot, Fleur A., additional, de Groen, Ruben A. L., additional, Kleij, Anne H. R., additional, Kirkegaard, Marina Knudsen, additional, Kamper, Peter, additional, Rasmussen, Peter Kristian, additional, von Buchwald, Christian, additional, de Nully Brown, Peter, additional, Kiilgaard, Jens Folke, additional, Vermaat, Joost S. P., additional, and Heegaard, Steffen, additional
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- 2024
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5. Machine Learning-Based Survival Prediction Models for Progression-Free and Overall Survival in Advanced-Stage Hodgkin Lymphoma
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Rask Kragh Jørgensen, Rasmus, Bergström, Fanny, Eloranta, Sandra, Tang Severinsen, Marianne, Bjøro Smeland, Knut, Fosså, Alexander, Haaber Christensen, Jacob, Hutchings, Martin, Bo Dahl-Sørensen, Rasmus, Kamper, Peter, Glimelius, Ingrid, E Smedby, Karin, K Parsons, Susan, Mae Rodday, Angie, J Maurer, Matthew, M Evens, Andrew, C El-Galaly, Tarec, Hjort Jakobsen, Lasse, Rask Kragh Jørgensen, Rasmus, Bergström, Fanny, Eloranta, Sandra, Tang Severinsen, Marianne, Bjøro Smeland, Knut, Fosså, Alexander, Haaber Christensen, Jacob, Hutchings, Martin, Bo Dahl-Sørensen, Rasmus, Kamper, Peter, Glimelius, Ingrid, E Smedby, Karin, K Parsons, Susan, Mae Rodday, Angie, J Maurer, Matthew, M Evens, Andrew, C El-Galaly, Tarec, and Hjort Jakobsen, Lasse
- Abstract
Purpose Patients diagnosed with advanced-stage Hodgkin lymphoma (aHL) have historically been risk-stratified using the International Prognostic Score (IPS). This study investigated if a machine learning (ML) approach could outperform existing models when it comes to predicting overall survival (OS) and progression-free survival (PFS). Patients and Methods This study used patient data from the Danish National Lymphoma Register for model development (development cohort). The ML model was developed using stacking, which combines several predictive survival models (Cox proportional hazard, flexible parametric model, IPS, principal component, penalized regression) into a single model, and was compared with two versions of IPS (IPS-3 and IPS-7) and the newly developed aHL international prognostic index (A-HIPI). Internal model validation was performed using nested cross-validation, and external validation was performed using patient data from the Swedish Lymphoma Register and Cancer Registry of Norway (validation cohort). Results In total, 707 and 760 patients with aHL were included in the development and validation cohorts, respectively. Examining model performance for OS in the development cohort, the concordance index (C-index) for the ML model, IPS-7, IPS-3, and A-HIPI was found to be 0.789, 0.608, 0.650, and 0.768, respectively. The corresponding estimates in the validation cohort were 0.749, 0.700, 0.663, and 0.741. For PFS, the ML model achieved the highest C-index in both cohorts (0.665 in the development cohort and 0.691 in the validation cohort). The time-varying AUCs for both the ML model and the A-HIPI were consistently higher in both cohorts compared with the IPS models within the first 5 years after diagnosis. Conclusion The new prognostic model for aHL on the basis of ML techniques demonstrated a substantial improvement compared with the IPS models, but yielded a limited improvement in predictive performance compared with the A-H, PURPOSE: Patients diagnosed with advanced-stage Hodgkin lymphoma (aHL) have historically been risk-stratified using the International Prognostic Score (IPS). This study investigated if a machine learning (ML) approach could outperform existing models when it comes to predicting overall survival (OS) and progression-free survival (PFS). PATIENTS AND METHODS: This study used patient data from the Danish National Lymphoma Register for model development (development cohort). The ML model was developed using stacking, which combines several predictive survival models (Cox proportional hazard, flexible parametric model, IPS, principal component, penalized regression) into a single model, and was compared with two versions of IPS (IPS-3 and IPS-7) and the newly developed aHL international prognostic index (A-HIPI). Internal model validation was performed using nested cross-validation, and external validation was performed using patient data from the Swedish Lymphoma Register and Cancer Registry of Norway (validation cohort). RESULTS: In total, 707 and 760 patients with aHL were included in the development and validation cohorts, respectively. Examining model performance for OS in the development cohort, the concordance index (C-index) for the ML model, IPS-7, IPS-3, and A-HIPI was found to be 0.789, 0.608, 0.650, and 0.768, respectively. The corresponding estimates in the validation cohort were 0.749, 0.700, 0.663, and 0.741. For PFS, the ML model achieved the highest C-index in both cohorts (0.665 in the development cohort and 0.691 in the validation cohort). The time-varying AUCs for both the ML model and the A-HIPI were consistently higher in both cohorts compared with the IPS models within the first 5 years after diagnosis. CONCLUSION: The new prognostic model for aHL on the basis of ML techniques demonstrated a substantial improvement compared with the IPS models, but yielded a limited improvement in predictive performance compared with the A-HIPI.
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- 2024
6. Long‐term cause‐specific mortality in adolescent and young adult Hodgkin lymphoma patients treated with contemporary regimens—A nationwide Danish cohort study.
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Rossetti, Sára, Juul, Sidsel Jacobsen, Eriksson, Frank, Warming, Peder Emil, Glinge, Charlotte, El‐Galaly, Tarec Christoffer, Haaber Christensen, Jacob, Kamper, Peter, Nully Brown, Peter, Gislason, Gunnar Hilmar, Vestmø Maraldo, Maja, Tfelt‐Hansen, Jacob, and Hutchings, Martin
- Abstract
Summary The documented treatment‐induced excess mortality in Hodgkin lymphoma (HL) has spurred important treatment changes over recent decades. This study aimed to examine mortality among young HL patients treated with contemporary strategies, including historical data comparison. This nationwide study included 1348 HL patients, diagnosed in 1995–2015 and aged 15–40 at diagnosis. Among the patients, 66.5% had Ann Arbor stage I–II and 33.5% had stage III–IV disease. With a median follow‐up of 14.76 years, 139 deaths occurred, yielding a 5‐year overall survival of 94.6%. Older age, advanced disease, earlier treatment periods and extensive regimens were associated with higher overall mortality risk. The cumulative risk of HL‐related death showed an initial sharp rise, with a plateau at 5.3% 10‐year post‐diagnosis. Deaths due to cardiovascular or pulmonary diseases and second cancers initially had minimal risk, gradually reaching 1.2% and 2.0% at the 20‐year mark respectively. HL cases had a 7.5‐fold higher mortality hazard than the background population. This study suggests that contemporary HL treatment still poses excess mortality risk, but recent changes have notably reduced overall and cause‐specific mortality compared to earlier eras. Balancing treatment efficacy and toxicity remains crucial, but our findings highlight improved outcomes with modern treatment approaches. [ABSTRACT FROM AUTHOR]
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- 2024
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