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Predicting Other-cause Mortality: The Minimalistic Approach
EUROPEAN UROLOGY 66 (2014) 1010–1011
available at www.sciencedirect.com journal homepage: www.europeanurology.com
Platinum Priority – Editorial Referring to the article published on pp. 1002–1009 of this issue
Predicting Other-cause Mortality: The Minimalistic Approach Briony K. Varda, Marianne Schmid, Quoc-Dien Trinh * Division of Urologic Oncology and Center for Surgery and Public Health, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
For the better part of the history of medicine, physicians have relied on clinical judgment to estimate a patient’s odds of benefiting from an intervention. On the one hand, there is little doubt that a healthy 50-yr-old man should be treated for locally advanced prostate cancer (PCa) or that an 89-yr-old man would best be kept on watchful waiting for very-low-risk PCa. On the other hand, for anything in between these outliers, clinicians rely on their intuition, which essentially amounts to a quasisubjective assessment and understanding of life expectancy weighted against the severity of comorbidities. Clinical judgment will vary between individual providers (interobserver variation) and may also vary within the same provider (intraobserver variation), depending on arbitrary criteria such as the time of the day and the cultural context. Such observations are troublesome, as patients deserve a more systematic and objective evaluation of their likelihood to benefit from a given treatment. Enter predictive tools, such as nomograms, lookup tables, and risk stratification models. Relying on weights attributed according to regression modeling, these predictive schemes can accurately estimate odds of end points such as the likelihood of other-cause mortality. Nomograms in particular have been shown to have high accuracy and to provide superior risk stratification compared with any other prediction tool [1]. As such, a plethora of investigators have created predictive models for PCa outcomes. As of 2007, during what was described as the golden age of nomograms [2], there were already >40 published tools addressing a variety of clinical scenarios related to PCa and predicting outcomes ranging from the risk of PCa based on the Prostate Health Index [3] to the odds of disease recurrence and mortality after radical prostatectomy [4].
Unfortunately, the use of predictive tools remains limited in our field. Many practitioners have complained that these tools are too complex to use daily. Although smartphone apps may have simplified the use of nomograms, early nomograms required physicians to use a pencil to connect lines and perform complex calculations. Even today, clicking on multiple drop-down menus and entering patient data can feel onerous. The sudden publication of so many predictive instruments has certainly contributed their demise. In light of this situation, the study by Daskivich et al. [5] in this issue of European Urology is both timely and a welcome addition to our field. In this retrospective cohort study, the authors compare the ability of weighted and unweighted Charlson comorbidity scores to predict othercause mortality in men with early-stage PCa. The authors show that Charlson scores are concordant across the two methods in nearly 90% of cases. Using a multivariate competing-risks model, they find that the unweighted score is nearly equivalent to that of the weighted instrument in predicting other-cause mortality for Charlson scores and age-adjusted Charlson indexes. Finally, they show that when there is score discordance, the unweighted method may actually be more clinically relevant, in that it improves predictive accuracy in men with the highest risk. Other than the need for external validation, this work makes great progress in simplifying risk stratification for early-stage PCa. In many ways, the study by Daskivich et al. [5] represents a best-case scenario. The authors have devised a predictive instrument that is both clinically accessible and accurate. Practically speaking, the results suggest that if a clinician has an accurate patient problem list, determining the risk of other-cause mortality should be straightforward. Perhaps
DOI of original article: http://dx.doi.org/10.1016/j.eururo.2014.05.029. * Corresponding author. Brigham and Women’s Hospital, Harvard Medical School, 45 Francis Street ASB II—3, Boston, MA 02115, USA. Tel. +1 617 525 7350; Fax: +1 617 525 6348. E-mail address: [email protected] (Q.-D. Trinh). http://dx.doi.org/10.1016/j.eururo.2014.08.013 0302-2838/# 2014 European Association of Urology. Published by Elsevier B.V. All rights reserved.
EUROPEAN UROLOGY 66 (2014) 1010–1011
the more important question is how the clinician uses this information to decide whom to treat. Nonetheless, the unweighted Charlson score represents a clinically relevant, easy-to-use, and accurate predictive tool. Conflicts of interest: The authors have nothing to disclose. Funding support: Quoc-Dien Trinh is supported by the Professor Walter Morris-Hale Distinguished Chair in Urologic Oncology at Brigham and Women’s Hospital.
References
1011
prostate cancer: a critical analysis of the literature. Clin Cancer Res 2008;14:4400–7. [2] Ross RW, Kantoff PW. Predicting outcomes in prostate cancer: how many more nomograms do we need? J Clin Oncol 2007;25:3563–4. [3] Lughezzani G, Lazzeri M, Haese A, et al. Multicenter European external validation of a prostate health index-based nomogram for predicting prostate cancer at extended biopsy. Eur Urol 2014; 66:906–12. [4] Punnen S, Freedland SJ, Presti Jr JC, et al. Multi-institutional validation of the CAPRA-S score to predict disease recurrence and mortality after radical prostatectomy. Eur Urol 2014;65:1171–7. [5] Daskivich TJ, Kwan L, Dash A, Greenfield S, Litwin MS. Weighted versus unweighted Charlson score to predict long-term other-cause
[1] Shariat SF, Karakiewicz PI, Suardi N, Kattan MW. Comparison of nomograms with other methods for predicting outcomes in
mortality in men with early-stage prostate cancer. Eur Urol 2014;66:1002–9.
available at www.sciencedirect.com journal homepage: www.europeanurology.com
Platinum Priority – Editorial Referring to the article published on pp. 1002–1009 of this issue
Predicting Other-cause Mortality: The Minimalistic Approach Briony K. Varda, Marianne Schmid, Quoc-Dien Trinh * Division of Urologic Oncology and Center for Surgery and Public Health, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
For the better part of the history of medicine, physicians have relied on clinical judgment to estimate a patient’s odds of benefiting from an intervention. On the one hand, there is little doubt that a healthy 50-yr-old man should be treated for locally advanced prostate cancer (PCa) or that an 89-yr-old man would best be kept on watchful waiting for very-low-risk PCa. On the other hand, for anything in between these outliers, clinicians rely on their intuition, which essentially amounts to a quasisubjective assessment and understanding of life expectancy weighted against the severity of comorbidities. Clinical judgment will vary between individual providers (interobserver variation) and may also vary within the same provider (intraobserver variation), depending on arbitrary criteria such as the time of the day and the cultural context. Such observations are troublesome, as patients deserve a more systematic and objective evaluation of their likelihood to benefit from a given treatment. Enter predictive tools, such as nomograms, lookup tables, and risk stratification models. Relying on weights attributed according to regression modeling, these predictive schemes can accurately estimate odds of end points such as the likelihood of other-cause mortality. Nomograms in particular have been shown to have high accuracy and to provide superior risk stratification compared with any other prediction tool [1]. As such, a plethora of investigators have created predictive models for PCa outcomes. As of 2007, during what was described as the golden age of nomograms [2], there were already >40 published tools addressing a variety of clinical scenarios related to PCa and predicting outcomes ranging from the risk of PCa based on the Prostate Health Index [3] to the odds of disease recurrence and mortality after radical prostatectomy [4].
Unfortunately, the use of predictive tools remains limited in our field. Many practitioners have complained that these tools are too complex to use daily. Although smartphone apps may have simplified the use of nomograms, early nomograms required physicians to use a pencil to connect lines and perform complex calculations. Even today, clicking on multiple drop-down menus and entering patient data can feel onerous. The sudden publication of so many predictive instruments has certainly contributed their demise. In light of this situation, the study by Daskivich et al. [5] in this issue of European Urology is both timely and a welcome addition to our field. In this retrospective cohort study, the authors compare the ability of weighted and unweighted Charlson comorbidity scores to predict othercause mortality in men with early-stage PCa. The authors show that Charlson scores are concordant across the two methods in nearly 90% of cases. Using a multivariate competing-risks model, they find that the unweighted score is nearly equivalent to that of the weighted instrument in predicting other-cause mortality for Charlson scores and age-adjusted Charlson indexes. Finally, they show that when there is score discordance, the unweighted method may actually be more clinically relevant, in that it improves predictive accuracy in men with the highest risk. Other than the need for external validation, this work makes great progress in simplifying risk stratification for early-stage PCa. In many ways, the study by Daskivich et al. [5] represents a best-case scenario. The authors have devised a predictive instrument that is both clinically accessible and accurate. Practically speaking, the results suggest that if a clinician has an accurate patient problem list, determining the risk of other-cause mortality should be straightforward. Perhaps
DOI of original article: http://dx.doi.org/10.1016/j.eururo.2014.05.029. * Corresponding author. Brigham and Women’s Hospital, Harvard Medical School, 45 Francis Street ASB II—3, Boston, MA 02115, USA. Tel. +1 617 525 7350; Fax: +1 617 525 6348. E-mail address: [email protected] (Q.-D. Trinh). http://dx.doi.org/10.1016/j.eururo.2014.08.013 0302-2838/# 2014 European Association of Urology. Published by Elsevier B.V. All rights reserved.
EUROPEAN UROLOGY 66 (2014) 1010–1011
the more important question is how the clinician uses this information to decide whom to treat. Nonetheless, the unweighted Charlson score represents a clinically relevant, easy-to-use, and accurate predictive tool. Conflicts of interest: The authors have nothing to disclose. Funding support: Quoc-Dien Trinh is supported by the Professor Walter Morris-Hale Distinguished Chair in Urologic Oncology at Brigham and Women’s Hospital.
References
1011
prostate cancer: a critical analysis of the literature. Clin Cancer Res 2008;14:4400–7. [2] Ross RW, Kantoff PW. Predicting outcomes in prostate cancer: how many more nomograms do we need? J Clin Oncol 2007;25:3563–4. [3] Lughezzani G, Lazzeri M, Haese A, et al. Multicenter European external validation of a prostate health index-based nomogram for predicting prostate cancer at extended biopsy. Eur Urol 2014; 66:906–12. [4] Punnen S, Freedland SJ, Presti Jr JC, et al. Multi-institutional validation of the CAPRA-S score to predict disease recurrence and mortality after radical prostatectomy. Eur Urol 2014;65:1171–7. [5] Daskivich TJ, Kwan L, Dash A, Greenfield S, Litwin MS. Weighted versus unweighted Charlson score to predict long-term other-cause
[1] Shariat SF, Karakiewicz PI, Suardi N, Kattan MW. Comparison of nomograms with other methods for predicting outcomes in
mortality in men with early-stage prostate cancer. Eur Urol 2014;66:1002–9.