Should We Use Nomograms to Predict Outcome?

Nomograms are key decision-making tools in prostate cancer radiation therapy

BACKGROUND

The use of nomograms for predicting clinical endpoints has been well documented. Nomograms provide an individualized prognosis and help clinicians determine the effectiveness of treatment for a given patient. Early identification of potential treatment failure or toxicity allows alternative approaches to be considered, reducing unnecessary treatment, morbidity, and cost. This review aims to evaluate clinical potential of nomogram use for the management of prostate cancer radiotherapy patients.

METHODS

PubMed, Embase, and Scopus were searched for literature published between 2006 and 2016. The reported correlation between measured and nomogram-predicted probabilities of biochemical control, disease progression, survival and toxicity was reviewed, through an analysis of concordance indexes and areas under the curves.

RESULTS

Sixteen studies were reviewed. Outcomes predicted by the nomogram were very close to outcomes measured (concordance index of 0.7 and above) in the majority. But a combination of under and overestimation of outcome was also reported. The predictive accuracy of nomograms was very variable, however, most nomograms had accuracy greater than chance, indicated by a concordance index higher than 0.5.

CONCLUSION

Nomograms can be used as prognostic guides to aid clinical decision-making for prostate cancer patients until further research addresses the limitations presented in this review. Strict definitions of end points should be added to future models and perhaps models could be enhanced with the incorporation of genomic variables or tumor specific parameters.

Predicting conversion from laparoscopic to open cholecystectomy presented as a probability nomogram based on preoperative patient risk factors

BACKGROUND

We aim to develop a risk stratification tool to preoperatively predict conversion (CONV) from a laparoscopic to open cholecystectomy.

METHODS

Multiple risk factors were analyzed with multivariate logistic regression and presented as probability nomograms.

RESULTS

Of 732 patients, 47 (6.4%) required CONV. Among 40 preoperative risk factors evaluated, 5 variables were found to have significant association with CONV: 2 clinical variables, previous upper abdominal surgery (odds ratio [OR] 95.2) and obesity defined as body mass index greater than 30 kg/m(2) (OR 12.3), and 3 ultrasound parameters, visible choledocholithiasis (OR 19.8), impacted stone at the neck of the gallbladder (OR 5.9), and gallbladder wall width in millimeters (OR 2.1). Nomograms based on this multivariate model demonstrate the individual preoperative probability of CONV. Internal validation using receiver operator curve analysis showed an area under the curve of .97.

CONCLUSION

Four probability nomograms were developed as a practical individual risk stratification tool to predict probability of CONV.

Prediction of cesarean delivery using the fetal-pelvic index

OBJECTIVE

The purpose of this study was to estimate the usefulness of the fetal-pelvic index (FPI) in the prediction of cesarean delivery among nulliparous and women who undergo a trial of labor after cesarean delivery (TOLAC).

STUDY DESIGN

This prospective cohort study included subjects at 2 hospitals from the University of Pennsylvania Health system. The study sample included nulliparous women and women who attempted TOLAC, with nonanomalous pregnancies at ≥37 weeks of gestation in vertex presentation (n = 221 and 207, respectively). FPI score was calculated with the ultrasound-based fetal biometric measures that were performed within 2 weeks of delivery and x-ray pelvimetry that was performed within 48 hours of delivery. Multivariable logistic regression was used to develop a clinical predictive index for cesarean delivery, which included FPI and clinical factors, in nulliparous women or women who attempted TOLAC. The prediction models were tested for accuracy with the area under the receiver operating characteristics curve.

RESULTS

Higher FPI scores were associated with greater odds of cesarean delivery. A unit increase in FPI score increased the odds of cesarean delivery by 15% (adjusted odds ratio, 1.15; 95% confidence interval, 1.09-1.21) for nulliparous women and 15% for women who attempted TOLAC (adjusted odds ratio, 1.15; 95% confidence interval, 1.10-1.20) after adjustment for maternal age, race, medical risk factors, and labor method. Among nulliparous women, the receiver operating characteristics analysis estimated an area under the curve of 0.88, with positive and negative predictive values of 76% and 87%, respectively. Similar findings were observed in the subgroup of women who attempted TOLAC.

CONCLUSION

The FPI when combined with clinical risk factors can identify accurately women who are at a high risk for cesarean delivery.

Cancer-specific survival after radical nephroureterectomy for upper urinary tract urothelial carcinoma: proposal and multi-institutional validation of a post-operative nomogram

Background:

Owing to the scarcity of upper urinary tract urothelial carcinoma (UUT-UC) it is often necessary for investigators to pool data. A patient-specific survival nomogram based on such data is needed to predict cancer-specific survival (CSS) post nephroureterectomy (NU). Herein, we propose and validate a nomogram to predict CSS post NU.

Patients and methods:

Twenty-one French institutions contributed data on 1120 patients treated with NU for UUT-UC. A total of 667 had full data for nomogram development. Study population was divided into the nomogram development cohort (397) and external validation cohort (270). Cox proportional hazards regression models were used for univariate and multivariate analyses and to build a nomogram. A reduced model selection was performed using a backward step-down selection process, and Harrell's concordance index (c-index) was used for quantifying the nomogram accuracy. Internal validation was performed by bootstrapping and the reduced nomogram model was calibrated.

Results:

Of the 397 patients in the nomogram development cohort, 91 (22.9%) died during follow-up, of which 66 (72.5%) died as a consequence of UUT-UC. The actuarial CSS probability at 5 years was 0.76 (95% CI, 71.62-80.94). On multivariate analysis, T stage (P<0.0001), N status (P=0.014), grade (P=0.026), age (P=0.005) and location (P=0.022) were associated with CSS. The reduced nomogram model had an accuracy of 0.78. We propose a nomogram to predict 3 and 5-year CSS post NU for UUT-UC.

Conclusion:

We have devised and validated an accurate nomogram (78%), superior to any single clinical variable or current model, for predicting 5-year CSS post NU for UUT-UC.