Jesper Bonnedahl
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Jesper Bonnedahl has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- David Robinson
Department of Urology Skåne University Hospital Malmö Sweden
1 shared publication - Hans Garmo
Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
1 shared publication - Marcus Westerberg
Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
1 shared publication - Marie Hjälm Eriksson
Department of Surgery and Oncology, Capio St. Görans Hospital, Karolinska Institute, Department of Pathology and Oncology, Stockholm, Sweden
1 shared publication - Pär Stattin
Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
1 shared publication - Rolf Gedeborg
Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
1 shared publication
Latest Publications
- Open Access
- 26 December 2025
- Published by Springer Nature in Scientific Reports
- Vol. 15 (1)
Optimised comorbidity indices can reflect patient performance status in register based studies of prostate cancer
Eastern Cooperative Oncology Group Performance Status (ECOG-PS) is commonly used in cancer trials to select a study population with good performance, but ECOG-PS is rarely available in health-care registers. We assessed if patient age and comorbidity indices can substitute ECOG-PS when selecting men in register-based studies of advanced prostate cancer. ECOG-PS data for 3966 men on androgen deprivation therapy for prostate cancer were retrieved from Prostate Cancer data Base Sweden. Logistic regression models were used to discriminate between ECOG-PS 0–1 versus 2–4 based on age, Charlson comorbidity index (CCI), a novel Multidimensional Diagnosis-based Comorbidity Index (MDCI) based on ICD codes, and a Drug Comorbidity Index (DCI) based on filled prescriptions. The model based on age, MDCI, and DCI provided the best discrimination (AUC = 0.82; 95% CI 0.81–0.84). In a hypothetical cohort of 1000 men where 750 men had ECOG-PS 0–1, 600 men would be included when excluding those with high risk of ECOG-PS 2–4 using this model and 60 of these would have ECOG 2–4 instead of 250 men if all 1000 men had been included. Age and two new comorbidity indices can with reasonable precision substitute ECOG-PS and help identify subsets of study populations likely to have favourable ECOG-PS.
- 26 December 2025
- Published by Springer Nature in Scientific Reports
- Vol. 15 (1)
Open AccessOptimised comorbidity indices can reflect patient performance status in register based studies of prostate cancer
Eastern Cooperative Oncology Group Performance Status (ECOG-PS) is commonly used in cancer trials to select a study population with good performance, but ECOG-PS is rarely available in health-care registers. We assessed if patient age and comorbidity indices can substitute ECOG-PS when selecting men in register-based studies of advanced prostate cancer. ECOG-PS data for 3966 men on androgen deprivation therapy for prostate cancer were retrieved from Prostate Cancer data Base Sweden. Logistic regression models were used to discriminate between ECOG-PS 0–1 versus 2–4 based on age, Charlson comorbidity index (CCI), a novel Multidimensional Diagnosis-based Comorbidity Index (MDCI) based on ICD codes, and a Drug Comorbidity Index (DCI) based on filled prescriptions. The model based on age, MDCI, and DCI provided the best discrimination (AUC = 0.82; 95% CI 0.81–0.84). In a hypothetical cohort of 1000 men where 750 men had ECOG-PS 0–1, 600 men would be included when excluding those with high risk of ECOG-PS 2–4 using this model and 60 of these would have ECOG 2–4 instead of 250 men if all 1000 men had been included. Age and two new comorbidity indices can with reasonable precision substitute ECOG-PS and help identify subsets of study populations likely to have favourable ECOG-PS.