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Sabine Siesling
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9 records found
1
Journal article
(2026)
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Elfi M. Verheul, Maria Margarete Karsten, Pimrapat Gebert, Lea Doppelbauer, Simona Borstnar, Sabine Siesling, Anne M. Stiggelbout, Judith Rietjens, Dirk Snelders, More Authors
BackgroundPredictions of Health-Related Quality of Life (HRQoL) outcomes could support realistic recovery expectations after breast cancer (BC) surgery. We aimed to develop and validate prediction models for HRQoL outcomes after BC surgery.MethodsWe used three datasets of BC patients from Berlin, Germany; Ljubljana, Slovenia; and Rotterdam; Netherlands. We included non-metastasised patients who were surgically treated for an initial diagnosis of BC and completed pre- and postoperative validated questionnaires. We used linear mixed models to analyse 15 domains of the EORTC QLQ-C30 and EORTC QLQ-BR23 over a two-year horizon. Baseline domain score (measured pre-operatively), age, BMI, smoking, TN stage, receptor status, neoadjuvant chemotherapy, axillary surgery and surgery type (breast-conserving, mastectomy, and immediate implant-based reconstruction) were included as predictors. Predictive performance at validation was assessed by the proportion of variance explained (marginal R2; mR2).ResultsWe included N = 795 patients from Germany for development and N = 623 from Slovenia and N = 417 from Netherlands for validation. The largest proportion of variance was explained by the prediction models for sexual functioning (SF, mR2 35%), physical functioning (PF, mR2 29%), body image (BI, mR2 26%), and cognitive functioning (CF, mR2 25%). The models captured meaningfully different trends over time for different outcomes and surgery types. The predictive performance of the models was largely driven by the baseline domain score. Performance was reasonable at external validation, with r2 values of 19–33% for PF, 10–17% for CF, 15–18% for BI, and 22–28% for SF, although some other outcomes (e.g. breast symptoms and role functioning) showed miscalibration, indicating a need for recalibration.ConclusionHRQoL after breast cancer surgery can be predicted using simple models with baseline domain scores and surgery type, demonstrating a new opportunity for Patient-Reported Outcome Measures (PROMs) in personalized care.
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BackgroundPredictions of Health-Related Quality of Life (HRQoL) outcomes could support realistic recovery expectations after breast cancer (BC) surgery. We aimed to develop and validate prediction models for HRQoL outcomes after BC surgery.MethodsWe used three datasets of BC patients from Berlin, Germany; Ljubljana, Slovenia; and Rotterdam; Netherlands. We included non-metastasised patients who were surgically treated for an initial diagnosis of BC and completed pre- and postoperative validated questionnaires. We used linear mixed models to analyse 15 domains of the EORTC QLQ-C30 and EORTC QLQ-BR23 over a two-year horizon. Baseline domain score (measured pre-operatively), age, BMI, smoking, TN stage, receptor status, neoadjuvant chemotherapy, axillary surgery and surgery type (breast-conserving, mastectomy, and immediate implant-based reconstruction) were included as predictors. Predictive performance at validation was assessed by the proportion of variance explained (marginal R2; mR2).ResultsWe included N = 795 patients from Germany for development and N = 623 from Slovenia and N = 417 from Netherlands for validation. The largest proportion of variance was explained by the prediction models for sexual functioning (SF, mR2 35%), physical functioning (PF, mR2 29%), body image (BI, mR2 26%), and cognitive functioning (CF, mR2 25%). The models captured meaningfully different trends over time for different outcomes and surgery types. The predictive performance of the models was largely driven by the baseline domain score. Performance was reasonable at external validation, with r2 values of 19–33% for PF, 10–17% for CF, 15–18% for BI, and 22–28% for SF, although some other outcomes (e.g. breast symptoms and role functioning) showed miscalibration, indicating a need for recalibration.ConclusionHRQoL after breast cancer surgery can be predicted using simple models with baseline domain scores and surgery type, demonstrating a new opportunity for Patient-Reported Outcome Measures (PROMs) in personalized care.
Journal article
(2024)
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Wouter Wolfkamp, Joyce Meijer, Jolanda C. van Hoeve, Felice van Erning, Lioe Fee de Geus-Oei, Ignace de Hingh, Jeroen Veltman, Sabine Siesling
Background: In the Netherlands, the COVID-19 pandemic resulted in a temporary halt of population screening for cancer and limited hospital capacity for non-COVID care. We aimed to investigate the impact of the pandemic on the in-hospital diagnostic pathway of breast cancer (BC) and colorectal cancer (CRC). Methods: 71,159 BC and 48,900 CRC patients were selected from the Netherlands Cancer Registry. Patients, diagnosed between January 2020 and July 2021, were divided into six periods and compared to the average of patients diagnosed in the same periods in 2017–2019. Diagnostic procedures performed were analysed using logistic regression. Lead time of the diagnostic pathway was analysed using Cox regression. Analyses were stratified for cancer type and corrected for age, sex (only CRC), stage and region. Results: For BC, less mammograms were performed during the first recovery period in 2020. More PET-CTs were performed during the first peak, first recovery and third peak period. For CRC, less ultrasounds and more CT scans and MRIs were performed during the first peak. Lead time decreased the most during the first peak by 2 days (BC) and 8 days (CRC). Significantly fewer patients, mainly in lower stages, were diagnosed with BC (−47%) and CRC (−36%) during the first peak. Conclusion: Significant impact of the COVID-19 pandemic was found on the diagnostic pathway, mainly during the first peak. In 2021, care returned to the same standards as before the pandemic. Long-term effects on patient outcomes are not known yet and will be the subject of future research.
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Background: In the Netherlands, the COVID-19 pandemic resulted in a temporary halt of population screening for cancer and limited hospital capacity for non-COVID care. We aimed to investigate the impact of the pandemic on the in-hospital diagnostic pathway of breast cancer (BC) and colorectal cancer (CRC). Methods: 71,159 BC and 48,900 CRC patients were selected from the Netherlands Cancer Registry. Patients, diagnosed between January 2020 and July 2021, were divided into six periods and compared to the average of patients diagnosed in the same periods in 2017–2019. Diagnostic procedures performed were analysed using logistic regression. Lead time of the diagnostic pathway was analysed using Cox regression. Analyses were stratified for cancer type and corrected for age, sex (only CRC), stage and region. Results: For BC, less mammograms were performed during the first recovery period in 2020. More PET-CTs were performed during the first peak, first recovery and third peak period. For CRC, less ultrasounds and more CT scans and MRIs were performed during the first peak. Lead time decreased the most during the first peak by 2 days (BC) and 8 days (CRC). Significantly fewer patients, mainly in lower stages, were diagnosed with BC (−47%) and CRC (−36%) during the first peak. Conclusion: Significant impact of the COVID-19 pandemic was found on the diagnostic pathway, mainly during the first peak. In 2021, care returned to the same standards as before the pandemic. Long-term effects on patient outcomes are not known yet and will be the subject of future research.
Journal article
(2021)
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Anna Z. De Boer, Esther Bastiaannet, Hein Putter, Perla J. Marang-van de Mheen, Sabine Siesling, Linda De Munck, Kelly M. De Ligt, Johanneke E.A. Portielje, Gerrit Jan Liefers, Nienke A. De Glas
Background: Individualized treatment in older patients with breast cancer can be improved by including comorbidity and other-cause mortality in prediction tools, as the other-cause mortality risk strongly increases with age. However, no optimal comorbidity score is established for this purpose. Therefore, this study aimed to compare the predictive value of the Charlson comorbidity index for other-cause mortality with the use of a simple comorbidity count and to assess the impact of frequently occurring comorbidities. Methods: Surgically treated patients with stages I-III breast cancer aged ≥70 years diagnosed between 2003 and 2009 were selected from the Netherlands Cancer Registry. Competing risk analysis was performed to associate 5-year other-cause mortality with the Charlson index, comorbidity count, and specific comorbidities. Discrimination and calibration were assessed. Results: Overall, 7511 patients were included. Twenty-nine percent had no comorbidities, and 59% had a Charlson score of 0. After five years, in 1974, patients had died (26%), of which 1450 patients without a distant recurrence (19%). Besides comorbidities included in the Charlson index, the psychiatric disease was strongly associated with other-cause mortality (sHR 2.44 (95%-CI 1.70-3.50)). The c-statistics of the Charlson index and comorbidity count were similar (0.65 (95%-CI 0.64-0.65) and 0.64 (95%-CI 0.64-0.65)). Conclusions: The predictive value of the Charlson index for 5-year other-cause mortality was similar to using comorbidity count. As it is easier to use in clinical practice, our findings indicate that comorbidity count can aid in improving individualizing treatment in older patients with breast cancer. Future studies should elicit whether geriatric parameters could improve prediction.
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Background: Individualized treatment in older patients with breast cancer can be improved by including comorbidity and other-cause mortality in prediction tools, as the other-cause mortality risk strongly increases with age. However, no optimal comorbidity score is established for this purpose. Therefore, this study aimed to compare the predictive value of the Charlson comorbidity index for other-cause mortality with the use of a simple comorbidity count and to assess the impact of frequently occurring comorbidities. Methods: Surgically treated patients with stages I-III breast cancer aged ≥70 years diagnosed between 2003 and 2009 were selected from the Netherlands Cancer Registry. Competing risk analysis was performed to associate 5-year other-cause mortality with the Charlson index, comorbidity count, and specific comorbidities. Discrimination and calibration were assessed. Results: Overall, 7511 patients were included. Twenty-nine percent had no comorbidities, and 59% had a Charlson score of 0. After five years, in 1974, patients had died (26%), of which 1450 patients without a distant recurrence (19%). Besides comorbidities included in the Charlson index, the psychiatric disease was strongly associated with other-cause mortality (sHR 2.44 (95%-CI 1.70-3.50)). The c-statistics of the Charlson index and comorbidity count were similar (0.65 (95%-CI 0.64-0.65) and 0.64 (95%-CI 0.64-0.65)). Conclusions: The predictive value of the Charlson index for 5-year other-cause mortality was similar to using comorbidity count. As it is easier to use in clinical practice, our findings indicate that comorbidity count can aid in improving individualizing treatment in older patients with breast cancer. Future studies should elicit whether geriatric parameters could improve prediction.
Impact of Older Age and Comorbidity on Locoregional and Distant Breast Cancer Recurrence
A Large Population-Based Study
Journal article
(2020)
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Anna Z. de Boer, Heleen C. van der Hulst, Nienke A. de Glas, Perla J. Marang-van de Mheen, Sabine Siesling, Linda de Munck, Kelly M. de Ligt, Johanneke E.A. Portielje, Esther Bastiaannet, Gerrit Jan Liefers
Background: Studies have demonstrated worse breast cancer-specific mortality with older age, despite an increasing risk of dying from other causes due to comorbidity (competing mortality). However, findings on the association between older age and recurrence risk are inconsistent. The aim of this study was to assess incidences of locoregional and distant recurrence by age, taking competing mortality into account. Materials and Methods: Patients surgically treated for nonmetastasized breast cancer between 2003 and 2009 were selected from The Netherlands Cancer Registry. Cumulative incidences of recurrence were calculated considering death without distant recurrence as competing event. Fine and Gray analyses were performed to characterize the impact of age (70–74 [reference group], 75–79, and ≥80 years) on recurrence risk. Results: A total of 18,419 patients were included. Nine-year cumulative incidences of locoregional recurrence were 2.5%, 3.1%, and 2.9% in patients aged 70–74, 75–79, and ≥80 years, and 9-year cumulative incidences of distant recurrence were 10.9%, 15.9%, and 12.7%, respectively. After adjustment for tumor and treatment characteristics, age was not associated with locoregional recurrence risk. For distant recurrence, patients aged 75–79 years remained at higher risk after adjustment for tumor and treatment characteristics (75–79 years subdistribution hazard ratio [sHR], 1.25; 95% confidence interval [CI], 1.11–1.41; ≥80 years sHR, 1.03; 95% CI, 0.91–1.17). Conclusion: Patients aged 75–79 years had a higher risk of distant recurrence than patients aged 70–74 years, despite the higher competing mortality. Individualizing treatment by using prediction tools that include competing mortality could improve outcome for older patients with breast cancer. Implications for Practice: In this population-based study of 18,419 surgically treated patients aged 70 years or older, patients aged 75–79 years were at higher risk of distant recurrence than were patients aged 70–74 years. This finding suggests that patients in this age category are undertreated. In contrast, it was also demonstrated that the risk of dying without a recurrence strongly increases with age, and patients with a high competing mortality risk are easily overtreated. To identify older patients who may benefit from more treatment, clinicians should therefore take competing mortality risk into account. Prediction tools could facilitate this and thereby improve treatment strategy.
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Background: Studies have demonstrated worse breast cancer-specific mortality with older age, despite an increasing risk of dying from other causes due to comorbidity (competing mortality). However, findings on the association between older age and recurrence risk are inconsistent. The aim of this study was to assess incidences of locoregional and distant recurrence by age, taking competing mortality into account. Materials and Methods: Patients surgically treated for nonmetastasized breast cancer between 2003 and 2009 were selected from The Netherlands Cancer Registry. Cumulative incidences of recurrence were calculated considering death without distant recurrence as competing event. Fine and Gray analyses were performed to characterize the impact of age (70–74 [reference group], 75–79, and ≥80 years) on recurrence risk. Results: A total of 18,419 patients were included. Nine-year cumulative incidences of locoregional recurrence were 2.5%, 3.1%, and 2.9% in patients aged 70–74, 75–79, and ≥80 years, and 9-year cumulative incidences of distant recurrence were 10.9%, 15.9%, and 12.7%, respectively. After adjustment for tumor and treatment characteristics, age was not associated with locoregional recurrence risk. For distant recurrence, patients aged 75–79 years remained at higher risk after adjustment for tumor and treatment characteristics (75–79 years subdistribution hazard ratio [sHR], 1.25; 95% confidence interval [CI], 1.11–1.41; ≥80 years sHR, 1.03; 95% CI, 0.91–1.17). Conclusion: Patients aged 75–79 years had a higher risk of distant recurrence than patients aged 70–74 years, despite the higher competing mortality. Individualizing treatment by using prediction tools that include competing mortality could improve outcome for older patients with breast cancer. Implications for Practice: In this population-based study of 18,419 surgically treated patients aged 70 years or older, patients aged 75–79 years were at higher risk of distant recurrence than were patients aged 70–74 years. This finding suggests that patients in this age category are undertreated. In contrast, it was also demonstrated that the risk of dying without a recurrence strongly increases with age, and patients with a high competing mortality risk are easily overtreated. To identify older patients who may benefit from more treatment, clinicians should therefore take competing mortality risk into account. Prediction tools could facilitate this and thereby improve treatment strategy.
Journal article
(2020)
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Erik Heeg, Perla J. Marang-van de Mheen, Marissa C. Van Maaren, Kay Schreuder, Rob A.E.M. Tollenaar, Sabine Siesling, Monique E.M.M. Bos, Marie Jeanne T.F.D. Vrancken Peeters
Delayed time to chemotherapy (TTC) is associated with decreased outcomes of breast cancer patients. Recently, studies suggested that the association might be subtype-dependent and that TTC within 30 days should be warranted in patients with triple-negative breast cancer (TNBC). The aim of the current study is to determine if TTC beyond 30 days is associated with reduced 10-year overall survival in TNBC patients. We identified all TNBC patients diagnosed between 2006 and 2014 who received adjuvant chemotherapy in the Netherlands. We distinguished between breast-conserving surgery (BCS) vs. mastectomy given the difference in preoperative characteristics and outcomes. The association was estimated with hazard ratios (HRs) using propensity-score matched Cox proportional hazard analyses. In total, 3,016 patients were included. In matched patients who underwent BCS (n = 904), 10-year overall survival was favorable for patients with TTC within 30 days (84.4% vs. 76.9%, p = 0.001). Patients with TTC beyond 30 days were more likely than those with TTC within 30 days to die within 10 years after surgery (HR 1.69 (95% CI 1.22–2.34), p = 0.002). In matched patients who underwent mastectomy (n = 1,568), there was no difference in 10 years overall survival between those with TTC within or beyond 30 days (74.5% vs. 74.7%, p = 0.716), nor an increased risk of death for those with TTC beyond 30 days (HR 1.04 (95% CI 0.84–1.28), p = 0.716). Initiation of adjuvant chemotherapy beyond 30 days is associated with decreased 10 years overall survival in TNBC patients who underwent BCS. Therefore, timelier initiation of chemotherapy in TNBC patients undergoing BCS seems warranted.
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Delayed time to chemotherapy (TTC) is associated with decreased outcomes of breast cancer patients. Recently, studies suggested that the association might be subtype-dependent and that TTC within 30 days should be warranted in patients with triple-negative breast cancer (TNBC). The aim of the current study is to determine if TTC beyond 30 days is associated with reduced 10-year overall survival in TNBC patients. We identified all TNBC patients diagnosed between 2006 and 2014 who received adjuvant chemotherapy in the Netherlands. We distinguished between breast-conserving surgery (BCS) vs. mastectomy given the difference in preoperative characteristics and outcomes. The association was estimated with hazard ratios (HRs) using propensity-score matched Cox proportional hazard analyses. In total, 3,016 patients were included. In matched patients who underwent BCS (n = 904), 10-year overall survival was favorable for patients with TTC within 30 days (84.4% vs. 76.9%, p = 0.001). Patients with TTC beyond 30 days were more likely than those with TTC within 30 days to die within 10 years after surgery (HR 1.69 (95% CI 1.22–2.34), p = 0.002). In matched patients who underwent mastectomy (n = 1,568), there was no difference in 10 years overall survival between those with TTC within or beyond 30 days (74.5% vs. 74.7%, p = 0.716), nor an increased risk of death for those with TTC beyond 30 days (HR 1.04 (95% CI 0.84–1.28), p = 0.716). Initiation of adjuvant chemotherapy beyond 30 days is associated with decreased 10 years overall survival in TNBC patients who underwent BCS. Therefore, timelier initiation of chemotherapy in TNBC patients undergoing BCS seems warranted.
Journal article
(2020)
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A. Z. de Boer, N. A. de Glas, P. J.Marang van de Mheen, O. M. Dekkers, S. Siesling, L. de Munck, K. M. de Ligt, G. J. Liefers, J. E.A. Portielje, E. Bastiaannet
Background: Surgery is increasingly being omitted in older patients with operable breast cancer in the Netherlands. Although omission of surgery can be considered in frail older patients, it may lead to inferior outcomes in non-frail patients. Therefore, the aim of this study was to evaluate the effect of omission of surgery on relative and overall survival in older patients with operable breast cancer. Methods: Patients aged 80 years or older diagnosed with stage I–II hormone receptor-positive breast cancer between 2003 and 2009 were selected from the Netherlands Cancer Registry. An instrumental variable approach was applied to minimize confounding, using hospital variation in rate of primary surgery. Relative and overall survival was compared between patients treated in hospitals with different rates of surgery. Results: Overall, 6464 patients were included. Relative survival was lower for patients treated in hospitals with lower compared with higher surgical rates (90·2 versus 92·4 per cent respectively after 5 years; 71·6 versus 88·2 per cent after 10 years). The relative excess risk for patients treated in hospitals with lower surgical rates was 2·00 (95 per cent c.i. 1·17 to 3·40). Overall survival rates were also lower among patients treated in hospitals with lower compared with higher surgical rates (48·3 versus 51·3 per cent after 5 years; 15·0 versus 19·7 per cent after 10 years respectively; adjusted hazard ratio 1·07, 95 per cent c.i. 1·00 to 1·14). Conclusion: Omission of surgery is associated with worse relative and overall survival in patients aged 80 years or more with stage I–II hormone receptor-positive breast cancer. Future research should focus on the effect on quality of life and physical functioning.
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Background: Surgery is increasingly being omitted in older patients with operable breast cancer in the Netherlands. Although omission of surgery can be considered in frail older patients, it may lead to inferior outcomes in non-frail patients. Therefore, the aim of this study was to evaluate the effect of omission of surgery on relative and overall survival in older patients with operable breast cancer. Methods: Patients aged 80 years or older diagnosed with stage I–II hormone receptor-positive breast cancer between 2003 and 2009 were selected from the Netherlands Cancer Registry. An instrumental variable approach was applied to minimize confounding, using hospital variation in rate of primary surgery. Relative and overall survival was compared between patients treated in hospitals with different rates of surgery. Results: Overall, 6464 patients were included. Relative survival was lower for patients treated in hospitals with lower compared with higher surgical rates (90·2 versus 92·4 per cent respectively after 5 years; 71·6 versus 88·2 per cent after 10 years). The relative excess risk for patients treated in hospitals with lower surgical rates was 2·00 (95 per cent c.i. 1·17 to 3·40). Overall survival rates were also lower among patients treated in hospitals with lower compared with higher surgical rates (48·3 versus 51·3 per cent after 5 years; 15·0 versus 19·7 per cent after 10 years respectively; adjusted hazard ratio 1·07, 95 per cent c.i. 1·00 to 1·14). Conclusion: Omission of surgery is associated with worse relative and overall survival in patients aged 80 years or more with stage I–II hormone receptor-positive breast cancer. Future research should focus on the effect on quality of life and physical functioning.
Journal article
(2019)
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Anna Z. de Boer, Esther Bastiaannet, Nienke A. de Glas, Perla J. Marang-van de Mheen, Olaf M. Dekkers, Sabine Siesling, Linda de Munck, Kelly M. de Ligt, Johanneke E.A. Portielje, Gerrit Jan Liefers
Purpose: In the Netherlands, radiotherapy after breast-conserving surgery (BCS) is omitted in up to 30% of patients aged ≥ 75 years. Although omission of radiotherapy is considered an option for older women treated with endocrine treatment, the majority of these patients do not receive systemic treatment following Dutch treatment guidelines. Therefore, the aim of this study was to evaluate the effect of omission of radiotherapy on locoregional recurrence risk in this patient population. Methods: Patients aged ≥ 75 years undergone BCS for T1-2N0 breast cancer diagnosed between 2003 and 2009 were selected from the Netherlands Cancer Registry. To minimize confounding by indication, hospital variation was used to assess the impact of radiotherapy-use on locoregional recurrence risk using cox proportional hazards regression. Hazards ratios with 95% confidence interval (CI) were estimated. Results: Overall, 2390 patients were included. Of the patients with hormone receptor-positive breast cancer, 39.3% received endocrine treatment. Five-year incidences of locoregional recurrence were 1.9%, 2.8%, and 3.0% in patients treated at hospitals with higher (average radiotherapy-use 96.0%), moderate (88.0%), and lower radiotherapy-use (72.2%) respectively, and nine-year incidences were 2.2%, 3.1%, and 3.2% respectively. Adjusted hazard ratios were 1.46 (95% CI 0.77–2.78) and 1.50 (95% CI 0.79–2.85) for patients treated at hospitals with moderate and lower radiotherapy-use, compared to patient treated at hospitals with higher radiotherapy-use. Conclusions: Despite endocrine treatment in only 39.3%, locoregional recurrence risk was low, even in patients treated at hospitals with lower radiotherapy-use. This provides reasonable grounds to consider omission of radiotherapy in patients aged ≥ 75 years with T1-2N0 breast cancer.
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Purpose: In the Netherlands, radiotherapy after breast-conserving surgery (BCS) is omitted in up to 30% of patients aged ≥ 75 years. Although omission of radiotherapy is considered an option for older women treated with endocrine treatment, the majority of these patients do not receive systemic treatment following Dutch treatment guidelines. Therefore, the aim of this study was to evaluate the effect of omission of radiotherapy on locoregional recurrence risk in this patient population. Methods: Patients aged ≥ 75 years undergone BCS for T1-2N0 breast cancer diagnosed between 2003 and 2009 were selected from the Netherlands Cancer Registry. To minimize confounding by indication, hospital variation was used to assess the impact of radiotherapy-use on locoregional recurrence risk using cox proportional hazards regression. Hazards ratios with 95% confidence interval (CI) were estimated. Results: Overall, 2390 patients were included. Of the patients with hormone receptor-positive breast cancer, 39.3% received endocrine treatment. Five-year incidences of locoregional recurrence were 1.9%, 2.8%, and 3.0% in patients treated at hospitals with higher (average radiotherapy-use 96.0%), moderate (88.0%), and lower radiotherapy-use (72.2%) respectively, and nine-year incidences were 2.2%, 3.1%, and 3.2% respectively. Adjusted hazard ratios were 1.46 (95% CI 0.77–2.78) and 1.50 (95% CI 0.79–2.85) for patients treated at hospitals with moderate and lower radiotherapy-use, compared to patient treated at hospitals with higher radiotherapy-use. Conclusions: Despite endocrine treatment in only 39.3%, locoregional recurrence risk was low, even in patients treated at hospitals with lower radiotherapy-use. This provides reasonable grounds to consider omission of radiotherapy in patients aged ≥ 75 years with T1-2N0 breast cancer.
Hospital transfer after a breast cancer diagnosis
A population-based study in the Netherlands of the extent, predictive characteristics and its impact on time to treatment
Journal article
(2019)
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E. Heeg, K. Schreuder, P. E.R. Spronk, J. C. Oosterwijk, P. J. Marang-van de Mheen, S. Siesling, M. T.F.D.Vrancken Peeters
Purpose: Patients may transfer of hospital for clinical reasons but this may delay time to treatment. The purpose of this study is to provide insight in the extent of hospital transfer in breast cancer care; which type of patients transfer and what is the impact on time to treatment. Methods: We included 41,413 breast cancer patients registered in the Netherlands Cancer Registry between 2014 and 2016. We investigated transfer of hospital between diagnosis and first treatment being surgery or neoadjuvant chemotherapy (NAC). Co-variate adjusted characteristics predictive for hospital transfer were determined. To adjust for possible treatment by indication bias we used propensity score matching (PSM). Time to treatment in patients with and without hospital transfer was compared. Results: Among 41,413 patients, 8.5% of all patients transferred to another hospital between diagnosis and first treatment; 4.9% before primary surgery and 24.8% before NAC. Especially young (aged <40 years) patients and those who underwent a mastectomy with immediate breast reconstruction (IBR) were more likely to transfer. The association of mastectomy with IBR with hospital transfer remained when using PSM. Hospital transfer after diagnosis significantly prolonged time to treatment; breast-conserving surgery by 5 days, mastectomy by 7 days, mastectomy with IBR by 9 days and NAC by 1 day. Conclusions: While almost 5% of Dutch patients treated with primary surgery transfer hospital after diagnosis and up to 25% for patients treated with NAC, our findings suggest that especially those treated with primary surgery are at risk for additional treatment delay by hospital transfer.
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Purpose: Patients may transfer of hospital for clinical reasons but this may delay time to treatment. The purpose of this study is to provide insight in the extent of hospital transfer in breast cancer care; which type of patients transfer and what is the impact on time to treatment. Methods: We included 41,413 breast cancer patients registered in the Netherlands Cancer Registry between 2014 and 2016. We investigated transfer of hospital between diagnosis and first treatment being surgery or neoadjuvant chemotherapy (NAC). Co-variate adjusted characteristics predictive for hospital transfer were determined. To adjust for possible treatment by indication bias we used propensity score matching (PSM). Time to treatment in patients with and without hospital transfer was compared. Results: Among 41,413 patients, 8.5% of all patients transferred to another hospital between diagnosis and first treatment; 4.9% before primary surgery and 24.8% before NAC. Especially young (aged <40 years) patients and those who underwent a mastectomy with immediate breast reconstruction (IBR) were more likely to transfer. The association of mastectomy with IBR with hospital transfer remained when using PSM. Hospital transfer after diagnosis significantly prolonged time to treatment; breast-conserving surgery by 5 days, mastectomy by 7 days, mastectomy with IBR by 9 days and NAC by 1 day. Conclusions: While almost 5% of Dutch patients treated with primary surgery transfer hospital after diagnosis and up to 25% for patients treated with NAC, our findings suggest that especially those treated with primary surgery are at risk for additional treatment delay by hospital transfer.
Journal article
(2018)
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Annemieke Witteveen, Gabriela F. Nane, Ingrid M.H. Vliegen, Sabine Siesling, Maarten J. IJzerman
Purpose. For individualized follow-up, accurate prediction of locoregional recurrence (LRR) and second primary (SP) breast cancer risk is required. Current prediction models employ regression, but with large data sets, machine-learning techniques such as Bayesian Networks (BNs) may be better alternatives. In this study, logistic regression was compared with different BNs, built with network classifiers and constraint- and score-based algorithms. Methods. Women diagnosed with early breast cancer between 2003 and 2006 were selected from the Netherlands Cancer Registry (NCR) (N = 37,320). BN structures were developed using 1) Bayesian network classifiers, 2) correlation coefficients with different cutoffs, 3) constraint-based learning algorithms, and 4) score-based learning algorithms. The different models were compared with logistic regression using the area under the receiver operating characteristic curve, an external validation set obtained from the NCR from 2007 and 2008 (N = 12,308), and subgroup analyses for a high- and low-risk group. Results. The BNs with the most links showed the best performance in both LRR and SP prediction (c-statistic of 0.76 for LRR and 0.69 for SP). In the external validation, logistic regression generally outperformed the BNs in both SP and LRR (c-statistic of 0.71 for LRR and 0.64 for SP). The differences were nonetheless small. Although logistic regression performed best on most parts of the subgroup analysis, BNs outperformed regression with respect to average risk for SP prediction in low- and high-risk groups. Conclusions. Although estimates of regression coefficients depend on other independent variables, there is no assumed dependence relationship between coefficient estimators and the change in value of other variables as in the case of BNs. Nonetheless, this analysis suggests that regression is still more accurate or at least as accurate as BNs for risk estimation for both LRRs and SP tumors.
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Purpose. For individualized follow-up, accurate prediction of locoregional recurrence (LRR) and second primary (SP) breast cancer risk is required. Current prediction models employ regression, but with large data sets, machine-learning techniques such as Bayesian Networks (BNs) may be better alternatives. In this study, logistic regression was compared with different BNs, built with network classifiers and constraint- and score-based algorithms. Methods. Women diagnosed with early breast cancer between 2003 and 2006 were selected from the Netherlands Cancer Registry (NCR) (N = 37,320). BN structures were developed using 1) Bayesian network classifiers, 2) correlation coefficients with different cutoffs, 3) constraint-based learning algorithms, and 4) score-based learning algorithms. The different models were compared with logistic regression using the area under the receiver operating characteristic curve, an external validation set obtained from the NCR from 2007 and 2008 (N = 12,308), and subgroup analyses for a high- and low-risk group. Results. The BNs with the most links showed the best performance in both LRR and SP prediction (c-statistic of 0.76 for LRR and 0.69 for SP). In the external validation, logistic regression generally outperformed the BNs in both SP and LRR (c-statistic of 0.71 for LRR and 0.64 for SP). The differences were nonetheless small. Although logistic regression performed best on most parts of the subgroup analysis, BNs outperformed regression with respect to average risk for SP prediction in low- and high-risk groups. Conclusions. Although estimates of regression coefficients depend on other independent variables, there is no assumed dependence relationship between coefficient estimators and the change in value of other variables as in the case of BNs. Nonetheless, this analysis suggests that regression is still more accurate or at least as accurate as BNs for risk estimation for both LRRs and SP tumors.