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4. Prognostic Models for Global Functional Outcome and Post-Concussion Symptoms Following Mild Traumatic Brain Injury: A Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study

Author

Mikolic, A, Steyerberg, E, Polinder, S, Wilson, L, Zeldovich, M, von Steinbueche, N, Newcombe, V, Menon, D, van der Naalt, J, Lingsma, H, Maas, A, van Klaveren, D, Akerlund, C, Amrein, K, Andelic, N, Andreassen, L, Anke, A, Antoni, A, Audibert, G, Azouvi, P, Azzolini, M, Bartels, R, Barzo, P, Beauvais, R, Beer, R, Bellander, B, Belli, A, Benali, H, Berardino, M, Beretta, L, Blaabjerg, M, Bragge, P, Brazinova, A, Brinck, V, Brooker, J, Brorsson, C, Buki, A, Bullinger, M, Cabeleira, M, Caccioppola, A, Calappi, E, Calvi, M, Cameron, P, Carbayo Lozano, G, Carbonara, M, Cavallo, S, Chevallard, G, Chieregato, A, Citerio, G, Clusmann, H, Coburn, M, Coles, J, Cooper, J, Correia, M, Covic, A, Curry, N, Czeiter, E, Czosnyka, M, Fizelier, C, Dark, P, Dawes, H, De Keyser, V, Degos, V, Della Corte, F, den Boogert, H, Depreitere, B, Dilvesi, D, Dixit, A, Donoghue, E, Dreier, J, Duliere, G, Ercole, A, Esser, P, Ezer, E, Fabricius, M, Feigin, V, Foks, K, Frisvold, S, Furmanov, A, Gagliardo, P, Galanaud, D, Gantner, D, Gao, G, George, P, Ghuysen, A, Giga, L, Glocker, B, Golubovic, J, Gomez, P, Gratz, J, Gravesteijn, B, Grossi, F, Gruen, R, Gupta, D, Haagsma, J, Haitsma, I, Helbok, R, Helseth, E, Horton, L, Huijben, J, Hutchinson, P, Jacobs, B, Jankowski, S, Jarrett, M, Jiang, J, Johnson, F, Jones, K, Karan, M, Kolias, A, Kompanje, E, Kondziella, D, Kornaropoulos, E, Koskinen, L, Kovacs, N, Kowark, A, Lagares, A, Lanyon, L, Laureys, S, Lecky, F, Ledoux, D, Lefering, R, Legrand, V, Lejeune, A, Levi, L, Lightfoot, R, Castano Leon, A, Maegele, M, Majdan, M, Manara, A, Manley, G, Martino, C, Marechal, H, Mattern, J, Mcmahon, C, Melegh, B, Menovsky, T, Misset, B, Muraleedharan, V, Murray, L, Negru, A, Nelson, D, Nieboer, D, Nyiradi, J, Olubukola, O, Oresic, M, Ortolano, F, Palotie, A, Parizel, P, Payen, J, Perera, N, Perlbarg, V, Persona, P, Peul, W, Piippo-Karjalainen, A, Pirinen, M, Pisica, D, Ples, H, Pomposo, I, Posti, J, Puybasset, L, Radoi, A, Ragauskas, A, Raj, R, Rambadagalla, M, Retel Helmrich, I, Rhodes, J, Richardson, S, Richter, S, Ripatti, S, Rocka, S, Roe, C, Roise, O, Rosand, J, Rosenfeld, J, Rosenlund, C, Rosenthal, G, Rossaint, R, Rossi, S, Rueckert, D, Rusnak, M, Sahuquillo, J, Sakowitz, O, Sanchez Porras, R, Sandor, J, Schafer, N, Schmidt, S, Schoechl, H, Schoonman, G, Schou, R, Schwendenwein, E, Sewalt, C, Skandsen, T, Smielewski, P, Sorinola, A, Stamatakis, E, Stanworth, S, Stevens, R, Stewart, W, Stocchetti, N, Sundstrom, N, Takala, R, Tamas, V, Tamosuitis, T, Taylor, M, Te Ao, B, Tenovuo, O, Theadom, A, Thomas, M, Tibboel, D, Timmers, M, Tolias, C, Trapani, T, Tudora, C, Unterberg, A, Vajkoczy, P, Vallance, S, Valeinis, E, Vamos, Z, van Der Jagt, M, Van Der Steen, G, van Der Naalt, J, van Dijck, J, van Essen, T, Van Hecke, W, van Heugten, C, Van Praag, D, van Veen, E, Vande Vyvere, T, van Wijk, R, Vargiolu, A, Vega, E, Velt, K, Verheyden, J, Vespa, P, Vik, A, Vilcinis, R, Volovici, V, von Steinbuchel, N, Voormolen, D, Vulekovic, P, Wang, K, Wiegers, E, Williams, G, Winzeck, S, Wolf, S, Yang, Z, Ylen, P, Younsi, A, Zeiler, F, Zelinkova, V, Ziverte, A, Zoerle, T, Mikolic A., Steyerberg E. W., Polinder S., Wilson L., Zeldovich M., von Steinbueche N., Newcombe V. F. J., Menon D. K., van der Naalt J., Lingsma H. F., Maas A. I. R., van Klaveren D., Akerlund C., Amrein K., Andelic N., Andreassen L., Anke A., Antoni A., Audibert G., Azouvi P., Azzolini M. L., Bartels R., Barzo P., Beauvais R., Beer R., Bellander B. -M., Belli A., Benali H., Berardino M., Beretta L., Blaabjerg M., Bragge P., Brazinova A., Brinck V., Brooker J., Brorsson C., Buki A., Bullinger M., Cabeleira M., Caccioppola A., Calappi E., Calvi M. R., Cameron P., Carbayo Lozano G., Carbonara M., Cavallo S., Chevallard G., Chieregato A., Citerio G., Clusmann H., Coburn M., Coles J., Cooper J. D., Correia M., Covic A., Curry N., Czeiter E., Czosnyka M., Fizelier C. D., Dark P., Dawes H., De Keyser V., Degos V., Della Corte F., den Boogert H., Depreitere B., Dilvesi D., Dixit A., Donoghue E., Dreier J., Duliere G. L., Ercole A., Esser P., Ezer E., Fabricius M., Feigin V. L., Foks K., Frisvold S., Furmanov A., Gagliardo P., Galanaud D., Gantner D., Gao G., George P., Ghuysen A., Giga L., Glocker B., Golubovic J., Gomez P. A., Gratz J., Gravesteijn B., Grossi F., Gruen R. L., Gupta D., Haagsma J. A., Haitsma I., Helbok R., Helseth E., Horton L., Huijben J., Hutchinson P. J., Jacobs B., Jankowski S., Jarrett M., Jiang J., Johnson F., Jones K., Karan M., Kolias A. G., Kompanje E., Kondziella D., Kornaropoulos E., Koskinen L. O., Kovacs N., Kowark A., Lagares A., Lanyon L., Laureys S., Lecky F., Ledoux D., Lefering R., Legrand V., Lejeune A., Levi L., Lightfoot R., Lingsma H., Castano Leon A. M., Maegele M., Majdan M., Manara A., Manley G., Martino C., Marechal H., Mattern J., McMahon C., Melegh B., Menon D., Menovsky T., Misset B., Muraleedharan V., Murray L., Negru A., Nelson D., Newcombe V., Nieboer D., Nyiradi J., Olubukola O., Oresic M., Ortolano F., Palotie A., Parizel P. M., Payen J. F., Perera N., Perlbarg V., Persona P., Peul W., Piippo-Karjalainen A., Pirinen M., Pisica D., Ples H., Pomposo I., Posti J. P., Puybasset L., Radoi A., Ragauskas A., Raj R., Rambadagalla M., Retel Helmrich I., Rhodes J., Richardson S., Richter S., Ripatti S., Rocka S., Roe C., Roise O., Rosand J., Rosenfeld J. V., Rosenlund C., Rosenthal G., Rossaint R., Rossi S., Rueckert D., Rusnak M., Sahuquillo J., Sakowitz O., Sanchez Porras R., Sandor J., Schafer N., Schmidt S., Schoechl H., Schoonman G., Schou R. F., Schwendenwein E., Sewalt C., Skandsen T., Smielewski P., Sorinola A., Stamatakis E., Stanworth S., Stevens R., Stewart W., Stocchetti N., Sundstrom N., Takala R., Tamas V., Tamosuitis T., Taylor M. S., Te Ao B., Tenovuo O., Theadom A., Thomas M., Tibboel D., Timmers M., Tolias C., Trapani T., Tudora C. M., Unterberg A., Vajkoczy P., Vallance S., Valeinis E., Vamos Z., van Der Jagt M., Van Der Steen G., van Der Naalt J., van Dijck J. T. J. M., van Essen T. A., Van Hecke W., van Heugten C., Van Praag D., van Veen E., Vande Vyvere T., van Wijk R. P. J., Vargiolu A., Vega E., Velt K., Verheyden J., Vespa P. M., Vik A., Vilcinis R., Volovici V., von Steinbuchel N., Voormolen D., Vulekovic P., Wang K. W., Wiegers E., Williams G., Winzeck S., Wolf S., Yang Z., Ylen P., Younsi A., Zeiler F. A., Zelinkova V., Ziverte A., Zoerle T., Mikolic, A, Steyerberg, E, Polinder, S, Wilson, L, Zeldovich, M, von Steinbueche, N, Newcombe, V, Menon, D, van der Naalt, J, Lingsma, H, Maas, A, van Klaveren, D, Akerlund, C, Amrein, K, Andelic, N, Andreassen, L, Anke, A, Antoni, A, Audibert, G, Azouvi, P, Azzolini, M, Bartels, R, Barzo, P, Beauvais, R, Beer, R, Bellander, B, Belli, A, Benali, H, Berardino, M, Beretta, L, Blaabjerg, M, Bragge, P, Brazinova, A, Brinck, V, Brooker, J, Brorsson, C, Buki, A, Bullinger, M, Cabeleira, M, Caccioppola, A, Calappi, E, Calvi, M, Cameron, P, Carbayo Lozano, G, Carbonara, M, Cavallo, S, Chevallard, G, Chieregato, A, Citerio, G, Clusmann, H, Coburn, M, Coles, J, Cooper, J, Correia, M, Covic, A, Curry, N, Czeiter, E, Czosnyka, M, Fizelier, C, Dark, P, Dawes, H, De Keyser, V, Degos, V, Della Corte, F, den Boogert, H, Depreitere, B, Dilvesi, D, Dixit, A, Donoghue, E, Dreier, J, Duliere, G, Ercole, A, Esser, P, Ezer, E, Fabricius, M, Feigin, V, Foks, K, Frisvold, S, Furmanov, A, Gagliardo, P, Galanaud, D, Gantner, D, Gao, G, George, P, Ghuysen, A, Giga, L, Glocker, B, Golubovic, J, Gomez, P, Gratz, J, Gravesteijn, B, Grossi, F, Gruen, R, Gupta, D, Haagsma, J, Haitsma, I, Helbok, R, Helseth, E, Horton, L, Huijben, J, Hutchinson, P, Jacobs, B, Jankowski, S, Jarrett, M, Jiang, J, Johnson, F, Jones, K, Karan, M, Kolias, A, Kompanje, E, Kondziella, D, Kornaropoulos, E, Koskinen, L, Kovacs, N, Kowark, A, Lagares, A, Lanyon, L, Laureys, S, Lecky, F, Ledoux, D, Lefering, R, Legrand, V, Lejeune, A, Levi, L, Lightfoot, R, Castano Leon, A, Maegele, M, Majdan, M, Manara, A, Manley, G, Martino, C, Marechal, H, Mattern, J, Mcmahon, C, Melegh, B, Menovsky, T, Misset, B, Muraleedharan, V, Murray, L, Negru, A, Nelson, D, Nieboer, D, Nyiradi, J, Olubukola, O, Oresic, M, Ortolano, F, Palotie, A, Parizel, P, Payen, J, Perera, N, Perlbarg, V, Persona, P, Peul, W, Piippo-Karjalainen, A, Pirinen, M, Pisica, D, Ples, H, Pomposo, I, Posti, J, Puybasset, L, Radoi, A, Ragauskas, A, Raj, R, Rambadagalla, M, Retel Helmrich, I, Rhodes, J, Richardson, S, Richter, S, Ripatti, S, Rocka, S, Roe, C, Roise, O, Rosand, J, Rosenfeld, J, Rosenlund, C, Rosenthal, G, Rossaint, R, Rossi, S, Rueckert, D, Rusnak, M, Sahuquillo, J, Sakowitz, O, Sanchez Porras, R, Sandor, J, Schafer, N, Schmidt, S, Schoechl, H, Schoonman, G, Schou, R, Schwendenwein, E, Sewalt, C, Skandsen, T, Smielewski, P, Sorinola, A, Stamatakis, E, Stanworth, S, Stevens, R, Stewart, W, Stocchetti, N, Sundstrom, N, Takala, R, Tamas, V, Tamosuitis, T, Taylor, M, Te Ao, B, Tenovuo, O, Theadom, A, Thomas, M, Tibboel, D, Timmers, M, Tolias, C, Trapani, T, Tudora, C, Unterberg, A, Vajkoczy, P, Vallance, S, Valeinis, E, Vamos, Z, van Der Jagt, M, Van Der Steen, G, van Der Naalt, J, van Dijck, J, van Essen, T, Van Hecke, W, van Heugten, C, Van Praag, D, van Veen, E, Vande Vyvere, T, van Wijk, R, Vargiolu, A, Vega, E, Velt, K, Verheyden, J, Vespa, P, Vik, A, Vilcinis, R, Volovici, V, von Steinbuchel, N, Voormolen, D, Vulekovic, P, Wang, K, Wiegers, E, Williams, G, Winzeck, S, Wolf, S, Yang, Z, Ylen, P, Younsi, A, Zeiler, F, Zelinkova, V, Ziverte, A, Zoerle, T, Mikolic A., Steyerberg E. W., Polinder S., Wilson L., Zeldovich M., von Steinbueche N., Newcombe V. F. J., Menon D. K., van der Naalt J., Lingsma H. F., Maas A. I. R., van Klaveren D., Akerlund C., Amrein K., Andelic N., Andreassen L., Anke A., Antoni A., Audibert G., Azouvi P., Azzolini M. L., Bartels R., Barzo P., Beauvais R., Beer R., Bellander B. -M., Belli A., Benali H., Berardino M., Beretta L., Blaabjerg M., Bragge P., Brazinova A., Brinck V., Brooker J., Brorsson C., Buki A., Bullinger M., Cabeleira M., Caccioppola A., Calappi E., Calvi M. R., Cameron P., Carbayo Lozano G., Carbonara M., Cavallo S., Chevallard G., Chieregato A., Citerio G., Clusmann H., Coburn M., Coles J., Cooper J. D., Correia M., Covic A., Curry N., Czeiter E., Czosnyka M., Fizelier C. D., Dark P., Dawes H., De Keyser V., Degos V., Della Corte F., den Boogert H., Depreitere B., Dilvesi D., Dixit A., Donoghue E., Dreier J., Duliere G. L., Ercole A., Esser P., Ezer E., Fabricius M., Feigin V. L., Foks K., Frisvold S., Furmanov A., Gagliardo P., Galanaud D., Gantner D., Gao G., George P., Ghuysen A., Giga L., Glocker B., Golubovic J., Gomez P. A., Gratz J., Gravesteijn B., Grossi F., Gruen R. L., Gupta D., Haagsma J. A., Haitsma I., Helbok R., Helseth E., Horton L., Huijben J., Hutchinson P. J., Jacobs B., Jankowski S., Jarrett M., Jiang J., Johnson F., Jones K., Karan M., Kolias A. G., Kompanje E., Kondziella D., Kornaropoulos E., Koskinen L. O., Kovacs N., Kowark A., Lagares A., Lanyon L., Laureys S., Lecky F., Ledoux D., Lefering R., Legrand V., Lejeune A., Levi L., Lightfoot R., Lingsma H., Castano Leon A. M., Maegele M., Majdan M., Manara A., Manley G., Martino C., Marechal H., Mattern J., McMahon C., Melegh B., Menon D., Menovsky T., Misset B., Muraleedharan V., Murray L., Negru A., Nelson D., Newcombe V., Nieboer D., Nyiradi J., Olubukola O., Oresic M., Ortolano F., Palotie A., Parizel P. M., Payen J. F., Perera N., Perlbarg V., Persona P., Peul W., Piippo-Karjalainen A., Pirinen M., Pisica D., Ples H., Pomposo I., Posti J. P., Puybasset L., Radoi A., Ragauskas A., Raj R., Rambadagalla M., Retel Helmrich I., Rhodes J., Richardson S., Richter S., Ripatti S., Rocka S., Roe C., Roise O., Rosand J., Rosenfeld J. V., Rosenlund C., Rosenthal G., Rossaint R., Rossi S., Rueckert D., Rusnak M., Sahuquillo J., Sakowitz O., Sanchez Porras R., Sandor J., Schafer N., Schmidt S., Schoechl H., Schoonman G., Schou R. F., Schwendenwein E., Sewalt C., Skandsen T., Smielewski P., Sorinola A., Stamatakis E., Stanworth S., Stevens R., Stewart W., Stocchetti N., Sundstrom N., Takala R., Tamas V., Tamosuitis T., Taylor M. S., Te Ao B., Tenovuo O., Theadom A., Thomas M., Tibboel D., Timmers M., Tolias C., Trapani T., Tudora C. M., Unterberg A., Vajkoczy P., Vallance S., Valeinis E., Vamos Z., van Der Jagt M., Van Der Steen G., van Der Naalt J., van Dijck J. T. J. M., van Essen T. A., Van Hecke W., van Heugten C., Van Praag D., van Veen E., Vande Vyvere T., van Wijk R. P. J., Vargiolu A., Vega E., Velt K., Verheyden J., Vespa P. M., Vik A., Vilcinis R., Volovici V., von Steinbuchel N., Voormolen D., Vulekovic P., Wang K. W., Wiegers E., Williams G., Winzeck S., Wolf S., Yang Z., Ylen P., Younsi A., Zeiler F. A., Zelinkova V., Ziverte A., and Zoerle T.

Abstract

After mild traumatic brain injury (mTBI), a substantial proportion of individuals do not fully recover on the Glasgow Outcome Scale Extended (GOSE) or experience persistent post-concussion symptoms (PPCS). We aimed to develop prognostic models for the GOSE and PPCS at 6 months after mTBI and to assess the prognostic value of different categories of predictors (clinical variables; questionnaires; computed tomography [CT]; blood biomarkers). From the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, we included participants aged 16 or older with Glasgow Coma Score (GCS) 13-15. We used ordinal logistic regression to model the relationship between predictors and the GOSE, and linear regression to model the relationship between predictors and the Rivermead Post-concussion Symptoms Questionnaire (RPQ) total score. First, we studied a pre-specified Core model. Next, we extended the Core model with other clinical and sociodemographic variables available at presentation (Clinical model). The Clinical model was then extended with variables assessed before discharge from hospital: early post-concussion symptoms, CT variables, biomarkers, or all three categories (extended models). In a subset of patients mostly discharged home from the emergency department, the Clinical model was extended with 2-3–week post-concussion and mental health symptoms. Predictors were selected based on Akaike’s Information Criterion. Performance of ordinal models was expressed as a concordance index (C) and performance of linear models as proportion of variance explained (R2). Bootstrap validation was used to correct for optimism. We included 2376 mTBI patients with 6-month GOSE and 1605 patients with 6-month RPQ. The Core and Clinical models for GOSE showed moderate discrimination (C = 0.68 95% confidence interval 0.68 to 0.70 and C = 0.70[0.69 to 0.71], respectively) and injury severity was the strongest predictor. The extended models had better

Published
2023

6. Discrepancy between disability and reported well-being after traumatic brain injury

Author

Retel Helmrich, I, van Klaveren, D, Andelic, N, Lingsma, H, Maas, A, Menon, D, Polinder, S, Røe, C, Steyerberg, E, Van Veen, E, Wilson, L, Citerio, G, Retel Helmrich IRA, van Klaveren D, Andelic N, Lingsma H, Maas A, Menon D, Polinder S, Røe C, Steyerberg EW, Van Veen E, Wilson L, Citerio G, Retel Helmrich, I, van Klaveren, D, Andelic, N, Lingsma, H, Maas, A, Menon, D, Polinder, S, Røe, C, Steyerberg, E, Van Veen, E, Wilson, L, Citerio, G, Retel Helmrich IRA, van Klaveren D, Andelic N, Lingsma H, Maas A, Menon D, Polinder S, Røe C, Steyerberg EW, Van Veen E, Wilson L, and Citerio G

Abstract

Background: Following traumatic brain injury (TBI), the clinical focus is often on disability. However, patients' perceptions of well-being can be discordant with their disability level, referred to as the 'disability paradox'. We aimed to examine the relationship between disability and health-related quality of life (HRQoL) following TBI, while taking variation in personal, injury-related and environment factors into account. Methods: We used data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury study. Disability was assessed 6 months post-injury by the Glasgow Outcome Scale-Extended (GOSE). HRQoL was assessed by the SF-12v2 physical and mental component summary scores and the Quality of Life after Traumatic Brain Injury overall scale. We examined mean total and domain HRQoL scores by GOSE. We quantified variance in HRQoL explained by GOSE, personal, injury-related and environment factors with multivariable regression. Results: Six-month outcome assessments were completed in 2075 patients, of whom 78% had mild TBI (Glasgow Coma Scale 13-15). Patients with severe disability had higher HRQoL than expected on the basis of GOSE alone, particularly after mild TBI. Up to 50% of patients with severe disability reported HRQoL scores within the normative range. GOSE, personal, injury-related and environment factors explained a limited amount of variance in HRQoL (up to 29%). Conclusion: Contrary to the idea that discrepancies are unusual, many patients with poor functional outcomes reported well-being that was at or above the boundary considered satisfactory for the normative sample. These findings challenge the idea that satisfactory HRQoL in patients with disability should be described as 'paradoxical' and question common views of what constitutes 'unfavourable' outcome.

Published
2022

8. Performance metrics for models designed to predict treatment effect

Author

Maas, C. C.H.M., Kent, D. M., Hughes, M. C., Dekker, R., Lingsma, H. F., van Klaveren, D., Maas, C. C.H.M., Kent, D. M., Hughes, M. C., Dekker, R., Lingsma, H. F., and van Klaveren, D.

Abstract

Background: Measuring the performance of models that predict individualized treatment effect is challenging because the outcomes of two alternative treatments are inherently unobservable in one patient. The C-for-benefit was proposed to measure discriminative ability. However, measures of calibration and overall performance are still lacking. We aimed to propose metrics of calibration and overall performance for models predicting treatment effect in randomized clinical trials (RCTs).Methods: Similar to the previously proposed C-for-benefit, we defined observed pairwise treatment effect as the difference between outcomes in pairs of matched patients with different treatment assignment. We match each untreated patient with the nearest treated patient based on the Mahalanobis distance between patient characteristics. Then, we define the Eavg-for-benefit, E50-for-benefit, and E90-for-benefit as the average, median, and 90th quantile of the absolute distance between the predicted pairwise treatment effects and local-regression-smoothed observed pairwise treatment effects. Furthermore, we define the cross-entropy-for-benefit and Brier-for-benefit as the logarithmic and average squared distance between predicted and observed pairwise treatment effects. In a simulation study, the metric values of deliberately “perturbed models” were compared to those of the data-generating model, i.e., “optimal model”. To illustrate these performance metrics, different modeling approaches for predicting treatment effect are applied to the data of the Diabetes Prevention Program: 1) a risk modelling approach with restricted cubic splines; 2) an effect modelling approach including penalized treatment interactions; and 3) the causal forest. Results: As desired, performance metric values of “perturbed models” were consistently worse than those of the “optimal model” (Eavg-for-benefi

Published
2023

10. Additional file 8 of Performance metrics for models designed to predict treatment effect

Author

Maas, C. C. H. M., Kent, D. M., Hughes, M. C., Dekker, R., Lingsma, H. F., and van Klaveren, D.

Abstract

Additional file 8. Calibration plots of pairwise treatment effect of simulated data from patients receiving metformin intervention. This Figure depicts observed versus predicted pairwise treatment effect by smoothed calibration curves (blue line) and quantiles of predicted pairwise treatment effect (black dots) of simulated data from the metformin versus placebo treatment. Observed pairwise treatment effect was obtained by matching patients based on patient characteristics. Smoothed calibration curves were obtained by local regression of the observed pairwise treatment effect of matched patient pairs on predicted pairwise treatment effect of matched patient pairs. For prediction of individualized treatment effect, we used a treatment effect modelling approach for the “optimal model” (panel A) and three “perturbed models” that overestimate average treatment effect (panel B), risk heterogeneity (panel C), and treatment effect heterogeneity (panel D). The average treatment effect is 6.6, 11.9, 6.6 (after a correction of with -0.085), and 6.6 (after a correction of with -0.16), respectively.

Published
2023
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11. Additional file 6 of Performance metrics for models designed to predict treatment effect

Author

Maas, C. C. H. M., Kent, D. M., Hughes, M. C., Dekker, R., Lingsma, H. F., and van Klaveren, D.

Abstract

Additional file 6. The probability of the potential outcome of diabetes under metformin treatment versus under control treatment predicted by the “optimal model”, and three “perturbed models” that overestimate average treatment effect, risk heterogeneity, and treatment effect heterogeneity.

Published
2023
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12. Additional file 7 of Performance metrics for models designed to predict treatment effect

Author

Maas, C. C. H. M., Kent, D. M., Hughes, M. C., Dekker, R., Lingsma, H. F., and van Klaveren, D.

Abstract

Additional file 7. Calibration plots of pairwise treatment effect of simulated data from patients receiving lifestyle intervention or metformin. This Figure depicts observed versus predicted pairwise treatment effect by smoothed calibration curves (blue line) and quantiles of predicted pairwise treatment effect (black dots) of simulated data from the lifestyle intervention or metformin versus placebo treatment. Observed pairwise treatment effect was obtained by matching patients based on patient characteristics. Smoothed calibration curves were obtained by local regression of the observed pairwise treatment effect of matched patient pairs on predicted pairwise treatment effect of matched patient pairs. For prediction of individualized treatment effect, we used the “perturbed model” that underestimates average treatment effect for lifestyle intervention (panel A) and metformin treatment (panel B). The average treatment effect is 7.1 and 3.5, respectively.

Published
2023
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16. Additional file 9 of Performance metrics for models designed to predict treatment effect

Author

Maas, C. C. H. M., Kent, D. M., Hughes, M. C., Dekker, R., Lingsma, H. F., and van Klaveren, D.

Abstract

Additional file 9. Calibration plot of pairwise treatment effect of training and test data of lifestyle intervention. This Figure depicts observed versus predicted pairwise treatment effect by smoothed calibration curves (blue line with 95% confidence interval displayed by grey shaded area) and quarters of predicted pairwise treatment effect (black dots) of lifestyle intervention versus placebo treatment. Observed pairwise treatment effect was obtained by matching patients based on patient characteristics. Smoothed calibration curves were obtained by local regression of the observed pairwise treatment effect of matched patient pairs on predicted pairwise treatment effect of matched patient pairs. For prediction of treatment effect, we used: a risk modelling approach (panel A; B), a treatment effect modelling approach (panel C; D), and a causal forest (panel E; F). The models are trained on 70 percent of the data (panel A; C; E) and evaluated on the other 30 percent of the data (B; D; F). Confidence intervals around the metric values were obtained using 100 bootstrap samples.

Published
2023
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17. Additional file 5 of Performance metrics for models designed to predict treatment effect

Author

Maas, C. C. H. M., Kent, D. M., Hughes, M. C., Dekker, R., Lingsma, H. F., and van Klaveren, D.

Abstract

Additional file 5. The probability of the potential outcome of diabetes under lifestyle intervention versus under control treatment predicted by the “optimal model”, and three “perturbed models” that overestimate average treatment effect, risk heterogeneity, and treatment effect heterogeneity.

Published
2023
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19. Explaining Outcome Differences between Men and Women following Mild Traumatic Brain Injury

Author

Mikolic, A, Groeniger, J, Zeldovich, M, Wilson, L, van Lennep, J, van Klaveren, D, Polinder, S, Citerio, G, Mikolic A, Groeniger JO, Zeldovich M, Wilson L, van Lennep JR, van Klaveren D, Polinder S, Citerio G, Mikolic, A, Groeniger, J, Zeldovich, M, Wilson, L, van Lennep, J, van Klaveren, D, Polinder, S, Citerio, G, Mikolic A, Groeniger JO, Zeldovich M, Wilson L, van Lennep JR, van Klaveren D, Polinder S, and Citerio G

Abstract

Men and women differ in outcomes following mild traumatic brain injury (TBI). In the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, we previously found that women had worse 6-month functional outcome (Glasgow Outcome Score Extended [GOSE]), health-related quality of life (HRQoL), and mental health following mild TBI. The aim of this study was to investigate whether those differences were mediated by psychiatric history, gender-related sociodemographic variables, or by care pathways. We analyzed sex/gender differences in 6-month GOSE, generic and TBI-specific HRQoL, and post-concussion and mental health symptoms using three sets of mediators: Psychiatric history, sociodemographic variables (living alone, living with children, education and employment status/job category), and care-pathways (referral to study hospital and discharge destination after emergency department); while controlling for a substantial number of potential confounders (pre-injury health and injury-related characteristics). We included 1842 men and 1022 women (16+) with a Glasgow Coma Score 13-15, among whom 83% had GOSE available and about 60% other 6-month outcomes. We used natural effects models to decompose the total effect of sex/gender on the outcomes into indirect effects that passed through the specified mediators and the remaining direct effects. In our study population, women had worse outcomes and these were only partly explained by psychiatric history, and not considerably explained by sociodemographic variables nor by care pathways. Factors other than differences in specified variables seem to underlie observed differences between men and women in outcomes after mild TBI. Future studies should explore more aspects of gender roles and identity and biological factors underpinning sex and gender differences in TBI outcomes.

Published
2021

20. Differences between Men and Women in Treatment and Outcome after Traumatic Brain Injury

Author

Mikolic, A, Van Klaveren, D, Groeniger, J, Wiegers, E, Lingsma, H, Zeldovich, M, Von Steinbuchel, N, Maas, A, Roeters Van Lennep, J, Polinder, S, Citerio, G, Mikolic A., Van Klaveren D., Groeniger J. O., Wiegers E. J. A., Lingsma H. F., Zeldovich M., Von Steinbuchel N., Maas A. I. R., Roeters Van Lennep J. E., Polinder S., Citerio G., Mikolic, A, Van Klaveren, D, Groeniger, J, Wiegers, E, Lingsma, H, Zeldovich, M, Von Steinbuchel, N, Maas, A, Roeters Van Lennep, J, Polinder, S, Citerio, G, Mikolic A., Van Klaveren D., Groeniger J. O., Wiegers E. J. A., Lingsma H. F., Zeldovich M., Von Steinbuchel N., Maas A. I. R., Roeters Van Lennep J. E., Polinder S., and Citerio G.

Abstract

Traumatic brain injury (TBI) is a significant cause of disability, but little is known about sex and gender differences after TBI. We aimed to analyze the association between sex/gender, and the broad range of care pathways, treatment characteristics, and outcomes following mild and moderate/severe TBI. We performed mixed-effects regression analyses in the prospective multi-center Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, stratified for injury severity and age, and adjusted for baseline characteristics. Outcomes were various care pathway and treatment variables, and 6-month measures of functional outcome, health-related quality of life (HRQoL), post-concussion symptoms (PCS), and mental health symptoms. The study included 2862 adults (36% women) with mild (mTBI; Glasgow Coma Scale [GCS] score 13-15), and 1333 adults (26% women) with moderate/severe TBI (GCS score 3-12). Women were less likely to be admitted to the intensive care unit (ICU; odds ratios [OR] 0.6, 95% confidence interval [CI]: 0.4-0.8) following mTBI. Following moderate/severe TBI, women had a shorter median hospital stay (OR 0.7, 95% CI: 0.5-1.0). Following mTBI, women had poorer outcomes; lower Glasgow Outcome Scale Extended (GOSE; OR 1.4, 95% CI: 1.2-1.6), lower generic and disease-specific HRQoL, and more severe PCS, depression, and anxiety. Among them, women under age 45 and above age 65 years showed worse 6-month outcomes compared with men of the same age. Following moderate/severe TBI, there was no difference in GOSE (OR 0.9, 95% CI: 0.7-1.2), but women reported more severe PCS (OR 1.7, 95% CI: 1.1-2.6). Men and women differ in care pathways and outcomes following TBI. Women generally report worse 6-month outcomes, but the size of differences depend on TBI severity and age. Future studies should examine factors that explain these differences.

Published
2021

21. Prediction of Global Functional Outcome and Post-Concussive Symptoms after Mild Traumatic Brain Injury: External Validation of Prognostic Models in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study

Author

Mikolic, A, Polinder, S, Steyerberg, E, Retel Helmrich, I, Giacino, J, Maas, A, Van Der Naalt, J, Voormolen, D, Von Steinbuchel, N, Wilson, L, Lingsma, H, Van Klaveren, D, Citerio, G, Mikolic A., Polinder S., Steyerberg E. W., Retel Helmrich I. R. A., Giacino J. T., Maas A. I. R., Van Der Naalt J., Voormolen D. C., Von Steinbuchel N., Wilson L., Lingsma H. F., Van Klaveren D., Citerio G., Mikolic, A, Polinder, S, Steyerberg, E, Retel Helmrich, I, Giacino, J, Maas, A, Van Der Naalt, J, Voormolen, D, Von Steinbuchel, N, Wilson, L, Lingsma, H, Van Klaveren, D, Citerio, G, Mikolic A., Polinder S., Steyerberg E. W., Retel Helmrich I. R. A., Giacino J. T., Maas A. I. R., Van Der Naalt J., Voormolen D. C., Von Steinbuchel N., Wilson L., Lingsma H. F., Van Klaveren D., and Citerio G.

Abstract

The majority of traumatic brain injuries (TBIs) are categorized as mild, according to a baseline Glasgow Coma Scale (GCS) score of 13-15. Prognostic models that were developed to predict functional outcome and persistent post-concussive symptoms (PPCS) after mild TBI have rarely been externally validated. We aimed to externally validate models predicting 3-12-month Glasgow Outcome Scale Extended (GOSE) or PPCS in adults with mild TBI. We analyzed data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) project, which included 2862 adults with mild TBI, with 6-month GOSE available for 2374 and Rivermead Post-Concussion Symptoms Questionnaire (RPQ) results available for 1605 participants. Model performance was evaluated based on calibration (graphically and characterized by slope and intercept) and discrimination (C-index). We validated five published models for 6-month GOSE and three for 6-month PPCS scores. The models used different cutoffs for outcome and some included symptoms measured 2 weeks post-injury. Discriminative ability varied substantially (C-index between 0.58 and 0.79). The models developed in the Corticosteroid Randomisation After Significant Head Injury (CRASH) trial for prediction of GOSE <5 discriminated best (C-index 0.78 and 0.79), but were poorly calibrated. The best performing models for PPCS included 2-week symptoms (C-index 0.75 and 0.76). In conclusion, none of the prognostic models for early prediction of GOSE and PPCS has both good calibration and discrimination in persons with mild TBI. In future studies, prognostic models should be tailored to the population with mild TBI, predicting relevant end-points based on readily available predictors.

Published
2021

23. Predicted and Observed Mortality at 10 Years in Patients With Bifurcation Lesions in the SYNTAX Trial

Author

Ninomiya, K., Serruys, P. W., Garg, S., Gao, C., Masuda, S., Lunardi, M., Lassen, J. F., Banning, A. P., Colombo, A., Burzotta, Francesco, Morice, M. -C., Mack, M. J., Holmes, D. R., Davierwala, P. M., Thuijs, D. J. F. M., van Klaveren, D., Onuma, Y., Burzotta F. (ORCID:0000-0002-6569-9401), Ninomiya, K., Serruys, P. W., Garg, S., Gao, C., Masuda, S., Lunardi, M., Lassen, J. F., Banning, A. P., Colombo, A., Burzotta, Francesco, Morice, M. -C., Mack, M. J., Holmes, D. R., Davierwala, P. M., Thuijs, D. J. F. M., van Klaveren, D., Onuma, Y., and Burzotta F. (ORCID:0000-0002-6569-9401)

Abstract

Background: Percutaneous coronary intervention (PCI) of bifurcation lesions is associated with higher rates of adverse events, and currently it is unclear whether PCI or coronary artery bypass grafting (CABG) is the safer treatment for these patients at very long-term follow-up. Objectives: The aim of this study was to investigate the impact of bifurcation lesions on individual predicted and observed all-cause 10-year mortality in the SYNTAX (Synergy Between PCI With Taxus and Cardiac Surgery) trial. Methods: In the SYNTAXES (SYNTAX Extended Survival) study, 10-year observed and individual predicted mortality derived from the SYNTAX score 2020 (SS-2020) was compared between patients with ≥1 bifurcation (n = 1,300) and those with no bifurcations (n = 487). Results: Among patients treated with PCI, patients with >1 bifurcation lesion compared with those without bifurcation lesions had a significantly higher risk for all-cause death (19.8% vs 30.1%; HR: 1.55; 95% CI: 1.12-2.14; P = 0.007), whereas following CABG, mortality was similar in patients with and those without bifurcation lesions (23.3% vs 23.0%; HR: 0.81; 95% CI: 0.59-1.12; P = 0.207; Pinteraction = 0.006). In PCI patients, a 2-stent vs a 1-stent technique was associated with higher mortality (33.3% vs 25.9%; HR: 1.51; 95% CI: 1.06-2.14; P = 0.021). According to the SS-2020, among those with ≥1 bifurcation, there was equipoise for all-cause mortality between PCI and CABG in 2 quartiles of the population, whereas CABG was superior to PCI in the 2 remaining quartiles. Conclusions: Bifurcation lesions require special attention from the heart team, considering the higher 10-year all-cause mortality associated with PCI. Careful evaluation of bifurcation lesion complexity and calculation of individualized 10-year prognosis using the SS-2020 may therefore be helpful in decision making. (Synergy Between PCI With TAXUS and Cardiac Surgery: SYNTAX Extended Survival [SYNTAXES], NCT03417050; Taxus Drug-Eluting Stent V

Published
2022

26. Performance of Heart Failure Clinical Prediction Models: A Systematic External Validation Study

Author

Hannah L. McGinnes, Benjamin S. Wessler, Ewout W. Steyerberg, Jenica N. Upshaw, James E. Udelson, Jinny G. Park, Jason Nelson, van Klaveren D, Benjamin Koethe, Van Calster B, Marvin A. Konstam, and David M. Kent

Subjects
medicine.medical_specialty, education.field_of_study, business.industry, Population, External validation, Patient data, medicine.disease, Clinical trial, Internal medicine, Heart failure, Cohort, medicine, Cardiology, Decision threshold, education, business, Predictive modelling
Abstract

BackgroundMost heart failure (HF) clinical prediction models (CPMs) have not been externally validated.MethodsWe performed a systematic review to identify CPMs predicting outcomes in HF, stratified by acute and chronic HF CPMs. External validations were performed using individual patient data from 8 large HF trials (1 acute, 7 chronic). CPM discrimination (c-statistic, % relative change in c-statistic), calibration (calibration slope, Harrell’s E, E90), and net benefit were evaluated for each CPM with and without recalibration.ResultsOf 135 HF CPMs screened, 24 (18%) were compatible with the population, predictors and outcomes to the trials and 42 external validations were performed (14 acute HF, 28 chronic HF). The median derivation c-statistic of acute HF CPMs was 0.76 (IQR, 0.75, 0.8), validation c-statistic was 0.67 (0.65, 0.68) and model-based c-statistic was 0.68 (0.66, 0.76), Hence, most of the apparent decrement in model performance was due to narrower case-mix in the validation cohort compared with the development cohort. The median derivation c-statistic for chronic HF CPMs was 0.76 (0.74, 0.8), validation c-statistic 0.61 (0.6, 0.63) and model-based c-statistic 0.68 (0.62, 0.71), suggesting that the decrement in model performance was only partially due to case-mix heterogeneity. Calibration was generally poor - median E (standardized by outcome rate) was 0.5 (0.4, 2.2) for acute HF CPMs and 0.5 (0.3, 0.7) for chronic HF CPMs. Updating the intercept alone led to a significant improvement in calibration in acute HF CPMs, but not in chronic HF CPMs. Net benefit analysis showed potential for harm in using CPMs when the decision threshold was not near the overall outcome rate but this improved with model recalibration.ConclusionsOnly a small minority of published CPMs contained variables and outcomes that were compatible with the clinical trial datasets. For acute HF CPMs, discrimination is largely preserved after adjusting for case-mix; however, the risk of net harm is substantial without model recalibration for both acute and chronic HF CPMs.

Published
2021

27. The Generalizability of Clinical Prediction Models for Patients with Acute Coronary Syndromes: Results from Independent External Validations

Author

Ewout W. Steyerberg, van Klaveren D, Van Calster B, Benjamin S. Wessler, David M. Kent, Jason Nelson, Hannah L. McGinnes, Jinny G. Park, and Jenica N. Upshaw

Subjects
Clinical trial, medicine.medical_specialty, Acute coronary syndrome, Calibration (statistics), business.industry, Emergency medicine, medicine, Generalizability theory, Patient data, business, medicine.disease, Predictive modelling, Statistic
Abstract

PurposeIt is increasingly recognized that clinical prediction models (CPMs) often do not perform as expected when they are tested on new databases. Independent external validations of CPMs are recommended but often not performed. Here we conduct independent external validations of acute coronary syndrome (ACS) CPMs.MethodsA systematic review identified CPMs predicting outcomes for patients with ACS. Independent external validations were performed by evaluating model performance using individual patient data from 5 large clinical trials. CPM performance with and without various recalibration techniques was evaluated with a focus on CPM discrimination (c-statistic, % relative change in c-statistic) as well as calibration (Harrell’s Eavg, E90, Net Benefit).ResultsOf 269 ACS CPMs screened, 23 (8.5%) were compatible with at least one of the trials and 28 clinically appropriate external validations were performed. The median c statistic of the CPMs in the derivation cohorts was 0.76 (IQR, 0.74 to 0.78). The median c-statistic in these external validations was 0.70 (IQR, 0.66 to 0.71) reflecting a 24% decrement in discrimination. However, this decrement in discrimination was due mostly to narrower case-mix in the validation cohorts compared to derivation cohorts, as reflected in the median model based c-statistic [0.71 (IQR 0.66 to 0.75). The median calibration slope in external validations was 0.84 (IQR, 0.72 to 0.98) and the median Eavg (standardized by the outcome rate) was 0.4 (IQR, 0.3 to 0.8). Net benefit indicates that most CPMs had a high risk of causing net harm when not recalibrated, particularly for decision thresholds not near the overall outcome rate.ConclusionIndependent external validations of published ACS CPMs demonstrate that models tested in our sample had relatively well-preserved discrimination but poor calibration when externally validated. Applying ‘off-the-shelf’ CPMs often risks net harm unless models are recalibrated to the populations on which they are used.

Published
2021

28. Daily practice in guideline adherence to adjuvant chemotherapy in stage III colon cancer and predictors of outcome: Adjuvant chemotherapy in stage III colon cancer patients

Author

MS Medische Oncologie, Cancer, van den Berg, I, van de Weerd, S, van Klaveren, D, Coebergh van den Braak, R R J, van Krieken, J H J M, Koopman, M, Roodhart, J M L, Medema, J P, IJzermans, J N M, MS Medische Oncologie, Cancer, van den Berg, I, van de Weerd, S, van Klaveren, D, Coebergh van den Braak, R R J, van Krieken, J H J M, Koopman, M, Roodhart, J M L, Medema, J P, and IJzermans, J N M

Published
2021

31. External Validations of Cardiovascular Clinical Prediction Models: A Large-scale Review of the Literature

Author

Wessler, Benjamin S., primary, Nelson, Jason, additional, Park, Jinny G., additional, McGinnes, Hannah, additional, Gulati, Gaurav, additional, Brazil, Riley, additional, Van Calster, Ben, additional, van Klaveren, D., additional, Venema, Esmee, additional, Steyerberg, Ewout, additional, Paulus, Jessica K., additional, and Kent, David M., additional

Published
2021
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33. Development and validation of a nomogram to predict recurrence and melanoma-specific mortality in patients with negative sentinel lymph nodes

Author

Verver, D, van Klaveren, D, Franke, V, van Akkooi, A C J, Rutkowski, P, Keilholz, U, Eggermont, A M M, Nijsten, T, Grünhagen, D J, Verhoef, C, Verver, D, van Klaveren, D, Franke, V, van Akkooi, A C J, Rutkowski, P, Keilholz, U, Eggermont, A M M, Nijsten, T, Grünhagen, D J, and Verhoef, C

Abstract

BACKGROUND: Patients with melanoma and negative sentinel nodes (SNs) have varying outcomes, dependent on several prognostic factors. Considering all these factors in a prediction model might aid in identifying patients who could benefit from a personalized treatment strategy. The objective was to construct and validate a nomogram for recurrence and melanoma-specific mortality (MSM) in patients with melanoma and negative SNs.METHODS: A total of 3220 patients with negative SNs were identified from a cohort of 4124 patients from four EORTC Melanoma Group centres who underwent sentinel lymph node biopsy. Prognostic factors for recurrence and MSM were studied with Cox regression analysis. Significant factors were incorporated in the models. Performance was assessed by discrimination (c-index) and calibration in cross-validation across the four centres. A nomogram was developed for graphical presentation.RESULTS: There were 3180 eligible patients. The final prediction model for recurrence and the calibrated model for MSM included three independent prognostic factors: ulceration, anatomical location and Breslow thickness. The c-index was 0·74 for recurrence and 0·76 for the calibrated MSM model. Cross-validation across the four centres showed reasonable model performance. A nomogram was developed based on these models. One-third of the patients had a 5-year recurrence probability of 8·2 per cent or less, and one-third had a recurrence probability of 23·0 per cent or more.CONCLUSION: A nomogram for predicting recurrence and MSM in patients with melanoma and negative SNs was constructed and validated. It could provide personalized estimates useful for tailoring surveillance strategies (reduce or increase intensity), and selection of patients for adjuvant therapy or clinical trials.

Published
2019

35. Risk stratification of sentinel node positive melanoma patients defines surgical management and adjuvant therapy treatment considerations

Author

Verver, D., primary, van Klaveren, D., additional, van Akkooi, A., additional, Rutkowski, P., additional, Powell, B., additional, Robert, C., additional, Testori, A., additional, van Leeuwen, B., additional, van der Veldt, A., additional, Keilholz, U., additional, Eggermont, A., additional, Verhoef, C., additional, and Grunhagen, D., additional

Published
2019
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36. Intraoperative Fistula Risk Score (iFRS) In Pancreatoduodenectomy: Development and Validation in Three Datasets

Author

Mungroop, T., primary, van Rijssen, L.B., additional, van Klaveren, D., additional, Smits, F.J., additional, van Woerden, V., additional, Linnemann, R., additional, Ecker, B.L., additional, van Dieren, S., additional, Bonsing, B., additional, Busch, O., additional, van Dam, R., additional, Erdmann, J., additional, van Eijck, C., additional, Gerhards, M., additional, van Goor, H., additional, van der Harst, E., additional, de Hingh, I., additional, de Jong, K., additional, Kazemier, G., additional, Luyer, M., additional, Shamali, A., additional, Barbaro, S., additional, Armstrong, T., additional, Takhar, A., additional, Hamady, Z., additional, Klaase, J., additional, Lips, D., additional, Molenaar, I.Q., additional, Nieuwenhuis, V., additional, Rupert, C., additional, van Santvoort, H., additional, Scheepers, J., additional, van der Schelling, G., additional, Vollmer, C., additional, Steyerberg, E., additional, Abu Hilal, M., additional, Groot Koerkamp, B., additional, and Besselink, M., additional

Published
2019
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38. P3179Exploring the value of the PRECISE-DAPT score after complex percutaneous coronary intervention to inform dual antiplatelet therapy duration decision-making

Author

Costa, F, primary, Van Klaveren, D, additional, Feres, F, additional, Raber, L, additional, Pilgrim, T, additional, Hong, M K, additional, Kim, H S, additional, Colombo, A, additional, Steg, P G, additional, Stone, G W, additional, Bhatt, D L, additional, Windecker, S, additional, Steyerberg, E, additional, and Valgimigli, M, additional

Published
2018
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39. Development and validation of a nomogram to predict recurrence and melanoma‐specific mortality in patients with negative sentinel lymph nodes.

Author

Verver, D., van Klaveren, D., Franke, V., van Akkooi, A. C. J., Rutkowski, P., Keilholz, U., Eggermont, A. M. M., Nijsten, T., Grünhagen, D. J., and Verhoef, C.

Subjects
*SENTINEL lymph nodes, *SENTINEL lymph node biopsy, *NOMOGRAPHY (Mathematics)
Abstract

Background: Patients with melanoma and negative sentinel nodes (SNs) have varying outcomes, dependent on several prognostic factors. Considering all these factors in a prediction model might aid in identifying patients who could benefit from a personalized treatment strategy. The objective was to construct and validate a nomogram for recurrence and melanoma‐specific mortality (MSM) in patients with melanoma and negative SNs. Methods: A total of 3220 patients with negative SNs were identified from a cohort of 4124 patients from four EORTC Melanoma Group centres who underwent sentinel lymph node biopsy. Prognostic factors for recurrence and MSM were studied with Cox regression analysis. Significant factors were incorporated in the models. Performance was assessed by discrimination (c‐index) and calibration in cross‐validation across the four centres. A nomogram was developed for graphical presentation. Results: There were 3180 eligible patients. The final prediction model for recurrence and the calibrated model for MSM included three independent prognostic factors: ulceration, anatomical location and Breslow thickness. The c‐index was 0·74 for recurrence and 0·76 for the calibrated MSM model. Cross‐validation across the four centres showed reasonable model performance. A nomogram was developed based on these models. One‐third of the patients had a 5‐year recurrence probability of 8·2 per cent or less, and one‐third had a recurrence probability of 23·0 per cent or more. Conclusion: A nomogram for predicting recurrence and MSM in patients with melanoma and negative SNs was constructed and validated. It could provide personalized estimates useful for tailoring surveillance strategies (reduce or increase intensity), and selection of patients for adjuvant therapy or clinical trials. Could personalize care [ABSTRACT FROM AUTHOR]

Published
2019
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40. Postoperative mortality after liver resection for perihilar cholangiocarcinoma: Importance of biliary drainage of the future liver remnant and development of a risk score

Author

Wiggers, J., primary, Groot Koerkamp, B., additional, van Klaveren, D., additional, Allen, P., additional, Besselink, M., additional, Busch, O., additional, D'Angelica, M., additional, Dematteo, R., additional, Kingham, P., additional, van Gulik, T., additional, and Jarnagin, W., additional

Published
2016
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41. Prediction of radial crossover in acute coronary syndromes

Author

Giuseppe Sangiorgi, Felice Gragnano, Luigi Fimiani, Giovanni Esposito, Salvatore Chianese, Shamir R. Mehta, Marco Valgimigli, Sergio Leonardi, Mattia Branca, Enrico Romagnoli, Dik Heg, Emanuele Monda, Pascal Vranckx, David van Klaveren, Giuseppe Gargiulo, Giuseppe Biondi-Zoccai, Paolo Calabrò, Vincenzo Fioretti, Giuseppe Andò, Stephan Windecker, Enrico Frigoli, Dario Di Maio, Sanjit S. Jolly, Gragnano, F., Jolly, S. S., Mehta, S., Branca, M., van Klaveren, D., Frigoli, E., Gargiulo, G., Leonardi, S., Vranckx, P., Di Maio, D., Monda, E., Fimiani, L., Fioretti, V., Chianese, S., Ando, G., Esposito, G., Sangiorgi, G. M., Biondi-Zoccai, G., Heg, D., Calabrò, Paolo, Windecker, S., Romagnoli, E., Valgimigli, M., and Public Health

Subjects
Femoral, medicine.medical_specialty, Radial, Crossover, Logistic regression, STEMI, Settore MED/11, Clinical Research, Internal medicine, medicine.artery, Medicine, Humans, Myocardial infarction, Derivation, Radial artery, Acute Coronary Syndrome, 610 Medicine & health, Killip class, Framingham Risk Score, ACS/NSTE-ACS, business.industry, Access site, medicine.disease, NSTEMI, medicine.anatomical_structure, Radial Artery, Cardiology, Cardiology and Cardiovascular Medicine, business, Artery, Human
Abstract

BACKGROUND The radial artery is recommended by international guidelines as the default vascular access in patients with acute coronary syndromes (ACS) managed invasively. However, crossover from radial to femoral access is required in 4-10% of cases and has been associated with worse outcomes. No standardised algorithm exists to predict the risk of radial crossover. AIMS We sought to derive and externally validate a risk score to predict radial crossover in patients with ACS managed invasively. METHODS The derivation cohort consisted of 4,197 patients with ACS undergoing invasive management via the randomly allocated radial access from the MATRIX trial. Using logistic regression, we selected predictors of radial crossover and developed a numerical risk score. External validation was accomplished among 3,451 and 491 ACS patients managed invasively and randomised to radial access from the RIVAL and RIFLE-STEACS trials, respectively. RESULTS The MATRIX score (age, height, smoking, renal failure, prior coronary artery bypass grafting, ST-segment elevation myocardial infarction, Killip class, radial expertise) showed a c-index for radial crossover of 0.71 (95% CI: 0.67-0.75) in the derivation cohort. Discrimination ability was modest in the RIVAL (c-index: 0.64; 95% CI: 0.59-0.67) and RIFLE-STEACS (c-index: 0.66; 95% CI: 0.57-0.75) cohorts. A cut-off of ≥41 points was selected to identify patients at high risk of radial crossover. CONCLUSIONS The MATRIX score is a simple eight-item risk score which provides a standardised tool for the prediction of radial crossover among patients with ACS managed invasively. This tool can assist operators in anticipating and better addressing difficulties related to transradial procedures, potentially improving outcomes.

Published
2021

42. Prediction of global functional outcome and post-concussive symptoms after mild Traumatic Brain Injury: external validation of prognostic models in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study

Author

Mikolic, Ana, Polinder, Suzanne, Steyerberg, Ewout W, Retel Helmrich, Isabel, Giacino, Joseph T., Maas, Andrew I.R., van der Naalt, Joukje, Voormolen, Daphne, von Steinbüchel, Nicole, Wilson, Lindsay, Lingsma, Hester F, van Klaveren, David, Andelic, Nada, Andreassen, Lasse, Anke, Audny, Frisvold, Shirin, Helseth, Eirik, Røe, Cecilie, Røise, Olav, Skandsen, Toril, Vik, Anne, Åkerlund, Cecilia, Amrein, Krisztina, Antoni, Anna, Audibert, Gerard, Azouvi, Philippe, Azzolini, Maria Luisa, Bartels, Ronald, Barzo, Pal, Beauvais, Romuald, Beer, Ronny, Bellander, Bo-Michael, Belli, Antonio, Benali, Habib, Berardino, Maurizio, Beretta, Luigi, Blaabjerg, Morten, Bragge, Peter, Brazinova, Alexandra, Brinck, Vibeke, Brooker, Joanne, Brorsson, Camilla, Buki, Andras, Bullinger, Monika, Cabeleira, Manuel, Caccioppola, Alessio, Calappi, Emiliana, Calvi, Maria Rosa, Cameron, Peter, Lozano, Guillermo Carbayo, Carbonara, Marco, CENTER-TBI Study Participants, Ragauskas, Arminas, Rocka, Saulius, Tamosuitis, Tomas, Vilcinis, Rimantas, Mary Ann Liebert, Centre of Excellence in Complex Disease Genetics, Aarno Palotie / Principal Investigator, Institute for Molecular Medicine Finland, Genomics of Neurological and Neuropsychiatric Disorders, HUS Neurocenter, Neurokirurgian yksikkö, Helsinki Institute for Information Technology, Statistical and population genetics, Department of Mathematics and Statistics, Biostatistics Helsinki, Clinicum, Helsinki University Hospital Area, Department of Public Health, Doctoral Programme in Clinical Research, Samuli Olli Ripatti / Principal Investigator, Complex Disease Genetics, University Management, Ročka, Saulius, Tamošuitis, Tomas, Mikolic, A, Polinder, S, Steyerberg, E, Retel Helmrich, I, Giacino, J, Maas, A, Van Der Naalt, J, Voormolen, D, Von Steinbuchel, N, Wilson, L, Lingsma, H, Van Klaveren, D, Citerio, G, Public Health, Mikolić, Ana, Polinder, Suzanne, Steyerberg, Ewout W, Retel Helmrich, Isabel R A, Giacino, Joseph T, Maas, Andrew I R, van der Naalt, Joukje, Voormolen, Daphne C, von Steinbüchel, Nicole, Wilson, Lindsay, Lingsma, Hester F, van Klaveren, David (Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study Participants and Investigators), Beretta, Luigi, Molecular Neuroscience and Ageing Research (MOLAR), Section Neuropsychology, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, and RS: FPN NPPP I

Subjects
Male, DISORDER, 030506 rehabilitation, Neurologi, Glasgow Outcome Scale, GUIDELINES, 3124 Neurology and psychiatry, 0302 clinical medicine, Epidemiology, Medicine, EPIDEMIOLOGY, prognostic model, Longitudinal Studies, Prospective Studies, Aged, 80 and over, education.field_of_study, Post-Concussion Syndrome, Head injury, Glasgow outcome scale extended, external validation, mild traumatic brain injury, post-concussive symptoms, Rivermead post-concussion symptoms questionnaire, Middle Aged, RECOVERY, Prognosis, 3. Good health, PREVALENCE, Neurology, Female, 0305 other medical science, Glasgow Outcome Scale Extended, Adult, medicine.medical_specialty, Adolescent, Traumatic brain injury, Population, BIOMARKERS, QUESTIONNAIRE, 03 medical and health sciences, Young Adult, Humans, Glasgow Coma Scale, education, Prognostic models, Brain Concussion, Aged, business.industry, 3112 Neurosciences, HEAD-INJURY, post-concussive symptom, Models, Theoretical, CARE, medicine.disease, PREVENTION, Reconstructive and regenerative medicine Radboud Institute for Health Sciences [Radboudumc 10], Physical therapy, Quality of Life, RISK-FACTORS, Neurology (clinical), Human medicine, business, 030217 neurology & neurosurgery
Abstract

The majority of traumatic brain injuries (TBIs) are categorized as mild, according to a baseline Glasgow Coma Scale (GCS) score of 13-15. Prognostic models that were developed to predict functional outcome and persistent post-concussive symptoms (PPCS) after mild TBI have rarely been externally validated. We aimed to externally validate models predicting 3-12-month Glasgow Outcome Scale Extended (GOSE) or PPCS in adults with mild TBI. We analyzed data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) project, which included 2862 adults with mild TBI, with 6-month GOSE available for 2374 and Rivermead Post-Concussion Symptoms Questionnaire (RPQ) results available for 1605 participants. Model performance was evaluated based on calibration (graphically and characterized by slope and intercept) and discrimination (C-index). We validated five published models for 6-month GOSE and three for 6-month PPCS scores. The models used different cutoffs for outcome and some included symptoms measured 2 weeks post-injury. Discriminative ability varied substantially (C-index between 0.58 and 0.79). The models developed in the Corticosteroid Randomisation After Significant Head Injury (CRASH) trial for prediction of GOSE, Funding Agencies:Hannelore Kohl Stiftung (Germany) OneMind (USA) Integra LifeSciences Corporation (USA) Neurotrauma Sciences (USA)

Published
2020

43. Differences between Men and Women in Treatment and Outcome after Traumatic Brain Injury

Author

Marek Majdan, Marina Zeldovich, Thomas Van Essen, Daniel Kondziella, Juan Sahuquillo, Oliver Sakowitz, Ana M Castaño-Leon, Matti Pirinen, Thijs Vande Vyvere, Giuseppe Citerio, Ana Mikolic, Jussi Posti, Renán Sánchez-Porras, Andreea Rădoi, Peter Hutchinson, Sandra Rossi, Pedro Gomez, Virginia Newcombe, William Stewart, Jonathan Coles, Frederick Zeiler, Aarno Palotie, Paul Dark, Arminas Ragauskas, Mikolic, A, Van Klaveren, D, Groeniger, J, Wiegers, E, Lingsma, H, Zeldovich, M, Von Steinbuchel, N, Maas, A, Roeters Van Lennep, J, Polinder, S, Citerio, G, Sociology, Public Health, Internal Medicine, Ragauskas, Arminas, Ročka, Saulius, Tamošuitis, Tomas, Vilcinis, Rimantas, CTR-TBI Participants, Rocka, Saulius, Tamosuitis, Tomas, Mary Ann Liebert, Section Neuropsychology, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, RS: FPN NPPP I, Mikolić, Ana, van Klaveren, David, Oude Groeniger, Joost, Wiegers, Eveline J A, Lingsma, Hester F, Zeldovich, Marina, von Steinbüchel, Nicole, Maas, Andrew I R, Roeters van Lennep, Jeanine E, Polinder, Suzanne (CENTER-TBI Participants and Investigators), Beretta, Luigi, Centre of Excellence in Complex Disease Genetics, Research Programs Unit, Aarno Palotie / Principal Investigator, Institute for Molecular Medicine Finland, Genomics of Neurological and Neuropsychiatric Disorders, HUS Neurocenter, Neurokirurgian yksikkö, Helsinki Institute for Information Technology, Statistical and population genetics, Department of Mathematics and Statistics, Biostatistics Helsinki, Clinicum, Helsinki University Hospital Area, Samuli Olli Ripatti / Principal Investigator, Complex Disease Genetics, and Molecular Neuroscience and Ageing Research (MOLAR)

Subjects
Male, sex differences, 030506 rehabilitation, Neurologi, VDP::Medisinske Fag: 700::Helsefag: 800::Epidemiologi medisinsk og odontologisk statistikk: 803, Glasgow Outcome Scale, outcomes, 3124 Neurology and psychiatry, CONCUSSION SYMPTOMS QUESTIONNAIRE, law.invention, 0302 clinical medicine, Quality of life, QUALITY-OF-LIFE, law, Brain Injuries, Traumatic, Prospective Studies, Depression (differential diagnoses), treatment, traumatic brain injury, Head injury, Age Factors, Middle Aged, Prognosis, DEPRESSION, Intensive care unit, PREVALENCE, 3. Good health, Intensive Care Units, Treatment Outcome, VDP::Medical disciplines: 700::Health sciences: 800::Epidemiology medical and dental statistics: 803, Neurology, outcome, Female, care pathway, SEX, HEALTH, 0305 other medical science, Adult, medicine.medical_specialty, Traumatic brain injury, sex difference, INTIMATE-PARTNER-VIOLENCE, Young Adult, 03 medical and health sciences, Sex Factors, SDG 3 - Good Health and Well-being, Internal medicine, medicine, Humans, Disabled Persons, Healthcare Disparities, Aged, GENDER-DIFFERENCES, business.industry, CENTER CARE, 3112 Neurosciences, HEAD-INJURY, Glasgow Coma Scale, Odds ratio, Length of Stay, MILD, medicine.disease, Quality of Life, Human medicine, Neurology (clinical), business, 030217 neurology & neurosurgery
Abstract

Traumatic brain injury (TBI) is a significant cause of disability, but little is known about sex and gender differences after TBI. We aimed to analyze the association between sex/gender, and the broad range of care pathways, treatment characteristics, and outcomes following mild and moderate/severe TBI. We performed mixed-effects regression analyses in the prospective multi-center Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study, stratified for injury severity and age, and adjusted for baseline characteristics. Outcomes were various care pathway and treatment variables, and 6-month measures of functional outcome, health-related quality of life (HRQoL), post-concussion symptoms (PCS), and mental health symptoms. The study included 2862 adults (36% women) with mild (mTBI; Glasgow Coma Scale [GCS] score 13–15), and 1333 adults (26% women) with moderate/severe TBI (GCS score 3–12). Women were less likely to be admitted to the intensive care unit (ICU; odds ratios [OR] 0.6, 95% confidence interval [CI]: 0.4-0.8) following mTBI. Following moderate/severe TBI, women had a shorter median hospital stay (OR 0.7, 95% CI: 0.5-1.0). Following mTBI, women had poorer outcomes; lower Glasgow Outcome Scale Extended (GOSE; OR 1.4, 95% CI: 1.2-1.6), lower generic and disease-specific HRQoL, and more severe PCS, depression, and anxiety. Among them, women under age 45 and above age 65 years showed worse 6-month outcomes compared with men of the same age. Following moderate/severe TBI, there was no difference in GOSE (OR 0.9, 95% CI: 0.7-1.2), but women reported more severe PCS (OR 1.7, 95% CI: 1.1-2.6). Men and women differ in care pathways and outcomes following TBI. Women generally report worse 6-month outcomes, but the size of differences depend on TBI severity and age. Future studies should examine factors that explain these differences Ana Mikolic´ et al., 2020; Published by Mary Ann Liebert, Inc. This Open Access article is distributed under the terms of the Creative Commons License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.

Published
2020

44. Comparative Methodological Assessment of the Randomized GLOBAL LEADERS Trial Using Total Ischemic and Bleeding Events

Author

Sergio Leandro, Jan G.P. Tijssen, Norihiro Kogame, Masafumi Ono, Christian W. Hamm, Johan Verbeeck, Margit Niethammer, Hideyuki Kawashima, Rutao Wang, David van Klaveren, Rodrigo Modolo, Chao Gao, Marco Valgimigli, Mariusz Tomaniak, Emanuele Barbato, Peter Jüni, Yoshinobu Onuma, Vasco Gama Ribeiro, Kuniaki Takahashi, Hironori Hara, Stephan Windecker, Géza Fontos, Faisal Sharif, Patrick W. Serruys, Ply Chichareon, Philippe Gabriel Steg, Michael Angioi, Hara, H., Van Klaveren, D., Takahashi, K., Kogame, N., Chichareon, P., Modolo, R., Tomaniak, M., Ono, M., Kawashima, H., Wang, R., Gao, C., Niethammer, M., Fontos, G., Angioi, M., Ribeiro, V. G., Barbato, E., Leandro, S., Hamm, C., Valgimigli, M., Windecker, S., Juni, P., Steg, P. G., Verbeeck, J., Tijssen, J. G. P., Sharif, F., Onuma, Y., Serruys, P. W., University of Zurich, Serruys, Patrick W, Graduate School, Cardiology, ACS - Heart failure & arrhythmias, ACS - Atherosclerosis & ischemic syndromes, ACS - Microcirculation, and Public Health

Subjects
medicine.medical_specialty, Time Factors, Endpoint Determination, aspirin, medicine.medical_treatment, Hemorrhage, 610 Medicine & health, Equivalence Trials as Topic, Revascularization, Rate ratio, Risk Assessment, 11171 Cardiocentro Ticino, 2705 Cardiology and Cardiovascular Medicine, ticagrelor, Risk Factors, Internal medicine, medicine, Humans, Myocardial infarction, Stroke, Aspirin, business.industry, Dual Anti-Platelet Therapy, Hazard ratio, percutaneous coronary intervention, Percutaneous coronary intervention, medicine.disease, mortality, Treatment Outcome, myocardial infarction, Research Design, Data Interpretation, Statistical, Cardiology, Cardiology and Cardiovascular Medicine, business, Ticagrelor, Platelet Aggregation Inhibitors, medicine.drug
Abstract

Background: Time-to-first-event analysis considers only the first event irrespective of its severity. There are several methods to assess trial outcomes beyond time-to-first-event analysis, such as analyzing total events and ranking outcomes. In the GLOBAL LEADERS study, time-to-first-event analysis did not show superiority of ticagrelor monotherapy following one-month dual antiplatelet therapy (DAPT) after percutaneous coronary intervention to conventional 12-month DAPT followed by aspirin monotherapy in the reduction of the primary composite end point of all-cause mortality or new Q-wave myocardial infarction. This study sought to explore various analytical approaches in assessing total ischemic and bleeding events after percutaneous coronary intervention in the GLOBAL LEADERS study. Methods and Results: Total ischemic and bleeding events were defined as all-cause mortality, any stroke, any myocardial infarction, any revascularization, or Bleeding Academic Research Consortium grade 2 or 3 bleeding. We used various analytical approaches to analyze the benefit of ticagrelor monotherapy over conventional DAPT. For ischemic and bleeding events at 2 years after percutaneous coronary intervention, ticagrelor monotherapy demonstrated a 6% risk reduction, compared with conventional 12-month DAPT in time-to-first-event analysis (hazard ratio, 0.94 [95% CI, 0.88–1.01]; log-rank P =0.10). In win ratio analysis, win ratio was 1.05 (95% CI, 0.97–1.13; P =0.20). Negative binomial regression and Andersen-Gill analyses which include repeated events showed statistically significant advantage for ticagrelor monotherapy (rate ratio, 0.92 [95% CI, 0.85–0.99; P =0.020] and hazard ratio, 0.92 [95% CI, 0.85–0.99; P =0.028], respectively), although in weighted composite end point analysis, the hazard ratio was 0.93 (95% CI, 0.84–1.04; log-rank P =0.22). Conclusions: Statistical analyses considering repeated events or event severity showed that ticagrelor monotherapy consistently reduced ischemic and bleeding events by 5% to 8%, compared with conventional 1-year DAPT. Applying multiple statistical methods could emphasize the multiple facets of a trial and result in accurate and more appropriate analyses. Considering the recurrence of ischemic and bleeding events, ticagrelor monotherapy appeared to be beneficial after percutaneous coronary intervention. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01813435.

Published
2020

45. Derivation and Validation of the PRECISE-HBR Score to Predict Bleeding After Percutaneous Coronary Intervention.

Author

Gragnano F, van Klaveren D, Heg D, Räber L, Krucoff MW, Raposeiras-Roubän S, Ten Berg JM, Leonardi S, Kimura T, Corpataux N, Spirito A, Hermiller JB, Abu-Assi E, Chan Pin Yin D, Azzahhafi J, Montalto C, Galazzi M, Bär S, Kavaliauskaite R, D'Ascenzo F, De Ferrari GM, Watanabe H, Steg PG, Bhatt DL, Calabrò P, Mehran R, Urban P, Pocock S, Windecker S, and Valgimigli M

Abstract

Background: Accurate bleeding risk stratification after percutaneous coronary intervention (PCI) is important for treatment individualization. However, there is still an unmet need for a more precise and standardized identification of high bleeding risk patients. We derived and validated a novel bleeding risk score by augmenting the PRECISE-DAPT score with the Academic Research Consortium for High Bleeding Risk (ARC-HBR) criteria., Methods: The derivation cohort comprised 29,188 patients undergoing PCI, of whom 1136 (3.9%) had a Bleeding Academic Research Consortium (BARC) 3 or 5 bleeding at 1 year, from four contemporary real-world registries and the XIENCE V USA trial. The PRECISE-DAPT score was refitted with a Fine-Gray model in the derivation cohort and extended with the ARC-HBR criteria. The primary outcome was BARC 3 or 5 bleeding within 1 year. Independent predictors of BARC 3 or 5 bleeding were selected at multivariable analysis (p<0.01). The discrimination of the score was internally assessed with apparent validation and cross-validation. The score was externally validated in 4578 patients from the MASTER DAPT trial and 5970 patients from the STOPDAPT-2 total cohort., Results: The PRECISE-HBR score (age, estimated glomerular filtration rate, hemoglobin, white-blood-cell count, previous bleeding, oral anticoagulation, and ARC-HBR criteria) showed an area under the curve (AUC) for 1-year BARC 3 or 5 bleeding of 0.73 (95% CI, 0.71-0.74) at apparent validation, 0.72 (95% CI, 0.70-0.73) at cross-validation, 0.74 (95% CI, 0.68-0.80) in the MASTER DAPT, and 0.73 (95% CI, 0.66-0.79) in the STOPDAPT-2, with superior discrimination than the PRECISE-DAPT (cross-validation: Δ AUC, 0.01; p=0.02; MASTER DAPT: Δ AUC, 0.05; p=0.004; STOPDAPT-2: Δ AUC, 0.02; p=0.20) and other risk scores. In the derivation cohort, a cut-off of 23 points identified 11,414 patients (39.1%) with a 1-year BARC 3 or 5 bleeding risk ≥4%. An alternative version of the score, including acute myocardial infarction on admission instead of white-blood-cell count, showed similar predictive ability., Conclusions: The PRECISE-HBR score is a contemporary, simple 7-item risk score to predict bleeding after PCI, offering a moderate improvement in discrimination over multiple existing scores. Further evaluation is required to assess its impact on clinical practice.

Published
2024
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46. Ten years survival benefit and appropriateness of surgical versus percutaneous revascularization in synergy between percutaneous coronary intervention with taxus and cardiac surgery randomized trial.

Author

Serruys PW, Ninomiya K, Revaiah PC, Gao C, Garg S, van Klaveren D, Onuma Y, Kappetein AP, Davierwala P, Mack M, Thuijs DJFM, Taggart DP, and Milojevic M

Abstract

Objectives: Average treatment effects from randomized trials do not reflect the heterogeneity of an individual's response to treatment. This study evaluates the appropriate proportions of patients for coronary artery bypass grafting, or percutaneous intervention based on the predicted/observed ratio of 10-year all-cause mortality in the SYNTAX population., Methods: The study included 1800 randomized patients and 1275 patients in the nested percutaneous (n = 198) or surgical (n = 1077) registries. The primary end-point was 10-year all-cause mortality. The SYNTAX score II-2020 was validated internally in the randomized cohort and externally in the registry cohort. Proportions of patients with survival benefits from coronary artery bypass grafting or percutaneous intervention were determined using SYNTAX score II-2020., Results: Ten-year mortality was 23.8% for coronary artery bypass grafting 28.6% for percutaneous intervention in the randomized cohort, 27.6% for coronary artery bypass grafting, and 55.4% for percutaneous intervention in the registries. In the coronary artery bypass grafting registry, the SYNTAX score II-2020 predicted 10-year mortality with helpful calibration and discrimination (C-index : 0.70, intercept : 0.00, slope : 0.76). The proportion of patients deriving a predicted survival benefit from coronary artery bypass grafting over percutaneous intervention was 82.4% (2143/2602) and 17.7% (459/2602) for the entire SYNTAX trial population; translating into a 4.7 to 1 appropriate ratio of treatment allocation to coronary artery bypass grafting and percutaneous intervention., Conclusions: Choosing a revascularization modality should depend on an individual's long-term prognosis rather than average treatment effects. Additionally, patients should be informed about their predicted prognosis., Trial Registration: Registered on clinicaltrial.govSYNTAXES: NCT03417050 (https://clinicaltrials.gov/ct2/show/NCT03417050);SYNTAX: NCT00114972 (https://www.clinicaltrials.gov/ct2/show/NCT00114972)., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery.)

Published
2024
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47. Guidance for unbiased predictive information for healthcare decision-making and equity (GUIDE): considerations when race may be a prognostic factor.

Author

Ladin K, Cuddeback J, Duru OK, Goel S, Harvey W, Park JG, Paulus JK, Sackey J, Sharp R, Steyerberg E, Ustun B, van Klaveren D, Weingart SN, and Kent DM

Abstract

Clinical prediction models (CPMs) are tools that compute the risk of an outcome given a set of patient characteristics and are routinely used to inform patients, guide treatment decision-making, and resource allocation. Although much hope has been placed on CPMs to mitigate human biases, CPMs may potentially contribute to racial disparities in decision-making and resource allocation. While some policymakers, professional organizations, and scholars have called for eliminating race as a variable from CPMs, others raise concerns that excluding race may exacerbate healthcare disparities and this controversy remains unresolved. The Guidance for Unbiased predictive Information for healthcare Decision-making and Equity (GUIDE) provides expert guidelines for model developers and health system administrators on the transparent use of race in CPMs and mitigation of algorithmic bias across contexts developed through a 5-round, modified Delphi process from a diverse 14-person technical expert panel (TEP). Deliberations affirmed that race is a social construct and that the goals of prediction are distinct from those of causal inference, and emphasized: the importance of decisional context (e.g., shared decision-making versus healthcare rationing); the conflicting nature of different anti-discrimination principles (e.g., anticlassification versus antisubordination principles); and the importance of identifying and balancing trade-offs in achieving equity-related goals with race-aware versus race-unaware CPMs for conditions where racial identity is prognostically informative. The GUIDE, comprising 31 key items in the development and use of CPMs in healthcare, outlines foundational principles, distinguishes between bias and fairness, and offers guidance for examining subgroup invalidity and using race as a variable in CPMs. This GUIDE presents a living document that supports appraisal and reporting of bias in CPMs to support best practice in CPM development and use., (© 2024. The Author(s).)

Published
2024
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48. Comparative effectiveness of 6x R-CHOP21 versus 6x R-CHOP21 + 2 R for patients with advanced-stage diffuse large B-cell lymphoma.

Author

Maas CCHM, van Klaveren D, Durmaz M, Visser O, Issa DE, Posthuma EFM, Zijlstra JM, Chamuleau MED, Lugtenburg PJ, Kersten MJ, and Dinmohamed AG

Subjects
Humans, Male, Female, Middle Aged, Aged, Adult, Aged, 80 and over, Neoplasm Staging, Treatment Outcome, Netherlands epidemiology, Lymphoma, Large B-Cell, Diffuse drug therapy, Lymphoma, Large B-Cell, Diffuse mortality, Antineoplastic Combined Chemotherapy Protocols therapeutic use, Rituximab therapeutic use, Rituximab administration & dosage, Vincristine therapeutic use, Vincristine administration & dosage, Cyclophosphamide therapeutic use, Cyclophosphamide administration & dosage, Doxorubicin therapeutic use, Doxorubicin administration & dosage, Prednisone therapeutic use, Prednisone administration & dosage
Abstract

First-line treatment for advanced-stage diffuse large B-cell lymphoma (DLBCL) typically involves 6x R-CHOP21 or 6x R-CHOP21 with two additional rituximab administrations (6x R-CHOP21 + 2 R). In contemporary practice, this treatment choice might be guided by interim PET scan results. This nationwide, population-based study investigates the comparative effectiveness of these treatment regimens in an era where interim PET-guided treatment decisions were not standard practice. Utilizing the Netherlands Cancer Registry, we identified 1577 adult patients diagnosed with advanced-stage DLBCL between 2014-2018 who completed either 6x R-CHOP21 (43%) or 6x R-CHOP21 + 2 R (57%). We used propensity scores to assess differences in event-free survival (EFS) and overall survival (OS). At five years, EFS (hazard ratio of 6x R-CHOP21 + 2 R versus 6x R-CHOP21 [HR] = 0.89; 95% confidence interval [CI], 0.72-1.09) and OS (HR = 0.93; 95% CI, 0.73-1.18) were not significantly different between both regimens. In exploratory risk-stratified analysis according to the International Prognostic Index (IPI), high-IPI patients (i.e., scores of 4-5) benefit most from 6x R-CHOP21 + 2 R (5-year absolute risk difference of EFS = 16.8%; 95% CI, -0.4%-34.1% and OS = 12.1%; 95% CI, -5.4-29.6%). Collectively, this analysis reveals no significant differences on average in EFS and OS between the two treatments. However, the potential benefits for high-risk patients treated with 6x R-CHOP21 + 2 R underscore the need for future research., (© 2024. The Author(s).)

Published
2024
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49. Experienced financial toxicity among long-term cancer survivors: results from a national cross-sectional survey.

Author

Klok JM, Duijts SFA, Engelen V, Masselink R, Dingemans AC, Aerts JGJV, Lingsma HF, and van Klaveren D

Abstract

Purpose: Financial toxicity, the subjective distress caused by objective financial burden, significantly impacts cancer survivors. Yet, enduring effects on survivors remain unclear. Therefore, we investigated the experienced objective financial burden and subjective financial distress in long-term cancer survivors., Methods: A cross-sectional nationwide online survey of adult cancer survivors ≥ 5y after diagnosis were analyzed. Objective financial burden was measured via extra expenses and income loss, while subjective financial distress covered psychological well-being, coping and support-seeking behavior, and financial concerns. Groups were compared (i.e., having cancer vs. former patients) by t-tests and chi-squared tests. Financial toxicity was visualized with Sankey plots and sunburst diagrams., Results: 4,675 respondents completed the survey, of whom 2,391 (51%) were ≥ 5y after their cancer diagnosis. Among them, 75% experienced income loss and/or extra expenses after diagnosis. One-third of the previously employed respondents relied on work disability benefits. Further, 'being unable to make ends meet' increased from 2% before diagnosis to 13% ≥ 5y after diagnosis (p < .001). Additionally, 58% reported negative psychological impacts of financial toxicity, and 47% worried about their financial future., Conclusions: Cancer survivors often face income loss and additional expenses, leading to ongoing financial difficulties that affect their psychological well-being. Despite this significant impact, there is a lack of guidance and support to help them manage these financial challenges. These findings highlight the need for healthcare professionals to recognize and address the financial challenges., Implications for Cancer Survivors: This study underscores the widespread financial challenges cancer survivors encounter, emphasizing the need for ongoing financial support and comprehensive assessments of their physical and psychological well-being., (© 2024. The Author(s).)

Published
2024
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50. Development and External Validation of a Prediction Model for Patients with Varicose Veins Suitable for Isolated Ambulatory Phlebectomy.

Author

Scheerders ERY, van Klaveren D, Malskat WSJ, van Rijn MJE, van der Velden SK, Nijsten T, and van den Bos RR

Subjects
Humans, Female, Male, Middle Aged, Treatment Outcome, Adult, Aged, Vascular Surgical Procedures methods, Vascular Surgical Procedures adverse effects, Reproducibility of Results, Predictive Value of Tests, Venous Insufficiency surgery, Venous Insufficiency physiopathology, Patient Selection, Risk Factors, Risk Assessment, Time Factors, Varicose Veins surgery, Saphenous Vein surgery, Ambulatory Surgical Procedures adverse effects, Ambulatory Surgical Procedures methods
Abstract

Objective: Isolated ambulatory phlebectomy is a potential treatment option for patients with an incompetent great saphenous vein (GSV) or anterior accessory saphenous vein and one or more incompetent tributaries. Being able to determine which patients will most likely benefit from isolated phlebectomy is important. This study aimed to identify predictors for avoidance of secondary axial ablation after isolated phlebectomy and to develop and externally validate a multivariable model for predicting this outcome., Methods: For model development, data from patients included in the SAPTAP trial were used. The investigated outcome was avoidance of ablation of the saphenous trunk one year after isolated ambulatory phlebectomy. Pre-defined candidate predictors were analysed with multivariable logistic regression. Predictors were selected using Akaike information criterion backward selection. Discriminative ability was assessed by the concordance index. Bootstrapping was used to correct regression coefficients, and the C index for overfitting. The model was externally validated using a population of 94 patients, with an incompetent GSV and one or more incompetent tributaries, who underwent isolated phlebectomy., Results: For model development, 225 patients were used, of whom 167 (74.2%) did not undergo additional ablation of the saphenous trunk one year after isolated phlebectomy. The final model consisted of three predictors for avoidance of axial ablation: tributary length (< 15 cm vs. > 30 cm: odds ratio [OR] 0.09, 95% confidence interval [CI] 0.02 - 0.40; 15 - 30 cm vs. > 30 cm: OR 0.18, 95% CI 0.09 - 0.38); saphenofemoral junction (SFJ) reflux (absent vs. present: OR 2.53, 95% CI 0.81 - 7.87); and diameter of the saphenous trunk (per millimetre change: OR 0.63, 95% CI 0.41 - 0.96). The discriminative ability of the model was moderate (0.72 at internal validation; 0.73 at external validation)., Conclusion: A model was developed for predicting avoidance of secondary ablation of the saphenous trunk one year after isolated ambulatory phlebectomy, which can be helpful in daily practice to determine the suitable treatment strategy in patients with an incompetent saphenous trunk and one or more incompetent tributaries. Patients having a longer tributary, smaller diameter saphenous trunk, and absence of terminal valve reflux in the SFJ are more likely to benefit from isolated phlebectomy., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Published
2024
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