How To Build and Interpret a Nomogram for Cancer Prognosis

Iasonos, Alexia; Schrag, Deborah; Raj, Ganesh V.; Panageas, Katherine S.

doi:10.1200/jco.2007.12.9791

Cited by 2,508 publications

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“…Survival probability was shown per prognostic group for each prediction period (30,90, and 365 days) ( Table 2) [2,19]. We developed a nomogram by ranking the effect estimates (b regression coefficients) of all factors independently associated with survival to a scale ranging from 0 to 100 points [17,20]. The predicted probability of 30-, 90-, and, 365-day survival were calculated for each patient using the multivariable Cox regression model underlying the nomogram [17,21].…”

Section: Resultsmentioning

confidence: 99%

“…Fulfilling four to five criteria corresponded to a 1-year survival probability of 0.5, two to three criteria to a 1-year survival probability of 0.25, and all patients who fulfilled none or only one criterion were deceased within 6 months after surgery [2]. Another frequently used tool to estimate survival in patients with cancer is the nomogram, which is a simple figure that generates an individualized numerical probability of survival based on a patient's unique set of characteristics; a number of points is assigned to each prognostic factor, which can be read from the nomogram and the sum of these points corresponds to a survival probability [17,20,25]. The nomogram can be seen as an extension of the classic scoring system.…”

Section: Introductionmentioning

confidence: 99%

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2015 Marshall Urist Young Investigator Award: Prognostication in Patients With Long Bone Metastases: Does a Boosting Algorithm Improve Survival Estimates?

Janssen

Heijden

Dijke

et al. 2015

Clin Orthop Relat Res

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Background Survival estimation guides surgical decisionmaking in metastatic bone disease. Traditionally, classic scoring systems, such as the Bauer score, provide survival estimates based on a summary score of prognostic factors. Identification of new factors might improve the accuracy of these models. Additionally, the use of different algorithms-nomograms or boosting algorithms-could further improve accuracy of prognostication relative to classic scoring systems. A nomogram is an extension of a classic scoring system and generates a more-individualized survival probability based on a patient's set of characteristics using a figure. Boosting is a method that automatically trains to classify outcomes by applying classifiers (variables) in a sequential way and subsequently combines them. A boosting algorithm provides survival probabilities based on every possible combination of variables. Questions/purposes We wished to (1) assess factors independently associated with decreased survival in patients with metastatic long bone fractures and (2) compare the accuracy of a classic scoring system, nomogram, and boosting algorithms in predicting 30-, 90-, and 365-day survival. Methods We included all 927 patients in our retrospective study who underwent surgery for a metastatic long bone fracture at two institutions between January 1999 and December 2013. We included only the first procedure if patients underwent multiple surgical procedures or had more than one fracture. Median followup was 8 months (interquartile range, 3-25 months); 369 of 412 (90%) patients who where alive at 1 year were still in followup. Multivariable Cox regression analysis was used to identify One author (SJ) certifies that he has received, an amount less than USD 10,000, from the Anna Foundation (Oegstgeest, The Netherlands), an amount less than USD 10,000 from the De Drie Lichten Foundation (Hilversum, The Netherlands), an amount less than USD 10,000 from the KWF Kankerbestrijding (Amsterdam, The Netherlands), and an amount less than USD 10,000, from the Michael van Vloten Foundation (Rotterdam, The Netherlands). One author (JS) certifies that he or a member of his family has or may receive payments or benefits, an amount less than USD 10,000, from Stryker (Kalamazoo, MI, USA), and an amount less than USD 10,000, from Biom'up (Saint-Priest, Lyon, France). All ICMJE Conflict of Interest Forms for authors and Clinical Orthopaedics and Related Research 1 editors and board members are on file with the publication and can be viewed on request. Each author certifies that his or her institution approved the human protocol for this investigation, that all investigations were conducted in conformity with ethical principles of research. This work was performed at Massachusetts General Hospital, Boston, MA, USA. clinical and laboratory factors independently associated with decreased survival. We created a classic scoring system, nomogram, and boosting algorithms based on identified variables. Accuracy of the algorithms was assessed using area unde...

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

2015 Marshall Urist Young Investigator Award: Prognostication in Patients With Long Bone Metastases: Does a Boosting Algorithm Improve Survival Estimates?

Janssen

Heijden

Dijke

et al. 2015

Clin Orthop Relat Res

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“…The model performance was evaluated with respect to discrimination and calibration. Discrimination was quantified in the form of concordance index (C-index), which was similar to the area under the receiver-operating characteristics (ROC) curves (18). The C-index was calculated using survConcordance function in rms package in R software and used to compare the performance between the nomogram and the TNM or VALSG staging systems.…”

Section: Validation and Calibration Of The Nomogrammentioning

confidence: 99%

Nomogram prediction for the survival of the patients with small cell lung cancer

et al. 2017

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Background: Small cell lung cancer (SCLC) is a subtype of lung cancer with poor prognosis. In this study, we aimed to build a nomogram to predict the survival of individual with SCLC by incorporating significant clinical parameters. Methods:The patients with SCLC were enrolled from the First Affiliated Hospital of Guangzhou Medical University (GMUFAH) between 2009 and 2013. We identified and incorporated the independent prognostic factors to build a nomogram to predict the survival of SCLC patients. The predictive accuracy and discriminative ability of the nomogram were evaluated by concordance index (C-index) and calibration curve.We also compared the accuracy of the built model with the 7 th AJCC TNM and VALSG staging system. The nomogram was further validated in an independent cohort of 80 patients with SCLC from Cancer Center of Guangzhou Medical University (GMUCC) between 2009 and 2013.Results: A total of 275 patients with SCLC were included in the primary cohort, and seven independent prognostic factors were identified including age, N stage, metastasis status, histology, platelets to lymphocyte ratio (PLR), neuron specific enolase (NSE) and CYFRA21-1 as independent prognostic factors after using Cox regression model. A nomogram incorporating these prognostic factors was subsequently built. The calibration curves for possibilities of 1-, 2-year overall survival (OS) revealed optimal agreement between nomogram prediction and actual observation. The C-index of this nomogram was higher than that of TNM Conclusions:In this study, we established and validated a novel nomogram for the prediction of OS for the patients with SCLC. This model could provide more accurate individual prediction of survival probability of SCLC than the existing staging systems.

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“…These nomograms differ from traditional prognostic models in several ways. 8 Variable selection is generally performed before model development, and is based on parameters that are believed to be clinically relevant, instead of relying on variables that retain significance on multivariable analysis. The latter approach may be suboptimal for maximizing predictive accuracy because this leads to predictor variable coefficients that are biased in high absolute value and confidence intervals (CIs) that are falsely narrow.…”

Section: Introductionmentioning

confidence: 99%

Nomogram for predicting survival in patients with unresectable and/or metastatic urothelial cancer who are treated with cisplatin‐based chemotherapy

Galsky

Moshier

Krege³

et al. 2013

Cancer

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BACKGROUND:The current study was conducted to develop a pretreatment prognostic model for patients with unresectable and/or metastatic urothelial cancer who were treated with first-line, cisplatin-based chemotherapy. METHODS: Individual data were pooled from 399 patients who were enrolled on 8 phase 2 and 3 trials evaluating cisplatin-based, first-line chemotherapy in patients with metastatic urothelial carcinoma. Variables selected for inclusion in the model were combined in a Cox proportional hazards model to produce a points-based nomogram with which to predict the median, 1-year, 2-year, and 5-year survival. The nomogram was validated externally using data from a randomized trial of the combination of methotrexate, vinblastine, doxorubicin plus cisplatin versus docetaxel plus cisplatin. RESULTS: The median survival of the development cohort was 13.8 months (95% confidence interval, 12.1 months-16.0 months); 68.2% of the patients had died at the time of last follow-up. On multivariable analysis, the number of visceral metastatic sites, Eastern Cooperative Oncology Group performance status, and leukocyte count were each found to be associated with overall survival (P <.05), whereas the site of the primary tumor and the presence of lymph node metastases were not. All 5 variables were included in the nomogram. When subjected to internal validation, the nomogram achieved a bootstrap-corrected concordance index of 0.626. When applied to the external validation cohort, the nomogram achieved a concordance index of 0.634. Calibration plots suggested that the nomogram was well calibrated for all predictions. CONCLUSIONS: Based on routinely measured pretreatment variables, a nomogram was constructed that predicts survival in patients with unresectable and/or metastatic urothelial cancer who are treated with cisplatin-based chemotherapy. This model may be useful in patient counseling and clinical trial design. Cancer 2013;119:3012-9. V C 2013 American Cancer Society.KEYWORDS: urothelial cancer; bladder cancer; prognosis; metastatic; chemotherapy; cisplatin. INTRODUCTIONContemporary cisplatin-based combination chemotherapy regimens achieve objective responses in approximately 50&percnt to 60% of patients with metastatic urothelial cancer.1,2 Although response durations are generally short, and the median overall survival of patients with unresectable and/or metastatic urothelial cancer is only approximately 14 months, significant heterogeneity exists with regard to patient outcomes.2 Long-term follow-up of clinical trials has demonstrated that approximately 10% to 20% of patients are alive at 5 years.1,3 The ability to predict individual patient outcomes has clear implications with regard to both patient counseling and patient stratification on clinical trials.Prognostic models have previously been developed for chemotherapy-naive patients with unresectable and/or metastatic urothelial cancer. In 1998, Bajorin et al identified Karnofsky performance status and the presence of visceral metastases as independent predictors ...

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How To Build and Interpret a Nomogram for Cancer Prognosis

Cited by 2,508 publications

References 27 publications

2015 Marshall Urist Young Investigator Award: Prognostication in Patients With Long Bone Metastases: Does a Boosting Algorithm Improve Survival Estimates?

2015 Marshall Urist Young Investigator Award: Prognostication in Patients With Long Bone Metastases: Does a Boosting Algorithm Improve Survival Estimates?

Nomogram prediction for the survival of the patients with small cell lung cancer

Nomogram for predicting survival in patients with unresectable and/or metastatic urothelial cancer who are treated with cisplatin‐based chemotherapy

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