Category: Clinical Stones: SWL

MP9-18 - Development and Validation of a Prediction Model for Shock Wave Lithotripsy Failure of Upper Urinary Tract Calculi Using Computed Tomography (CT) Data

Fri, Sep 21
2:00 PM - 4:00 PM

Introduction & Objective : For treatment of a solitary upper urinary tract calculus, extracorporeal shock wave lithotripsy (SWL) or ureteroscopic lithotripsy (URSL) is the first treatment option. However, there are no clinical prediction models that are routinely used as tools to select either SWL or URSL. We have developed and validated a clinical prediction model that accurately predicts SWL failure by considering computed tomography (CT) data.


Methods :

Research design: Retrospective cohort study


Setting: Patients diagnosed with upper urinary tract calculi by CT in 5 hospitals in Japan between January 1 2006 and December 31 2016. In this setting, 3,886 patients were considered.


Candidate predictors: Eight predictors were selected: age, sex, presence of colic, localization of calculus, stone size, skin-to-stone distance, stone radiodensity, and hydronephrosis.


Main outcome measures: SWL failure was defined as cases that were not resolved within 3 SWL sessions.


Calibration and discrimination: Model calibration was evaluated by calibration slope and Hosmer-Lemeshow goodness of fit test (HL test). Discrimination was evaluated by receiver operating characteristic curve and c statistics.


Statistical analysis: Multivariable logistic regression analysis was performed. Based on the estimated β-coefficients, predictive scores were created.


Results : In total, 2,271 of 3,886 patients were included. Patients were divided into the development cohort (1,666 cases) and validation cohort (605 cases) based on geographical factors. We developed a clinical prediction model consisting of scores between 0 and 68 points. As a result of internal validation, optimism-correlated c-statistic was 0.73. In the validation cohort, HL test showed that P -value was 0.13, and c-statistic was 0.74 (95% confidence intervals, 0.69–0.79).


Conclusions :

We have developed and validated a new clinical prediction model for SWL failure by using CT data. This model has a relatively high predictive performance, which may its use as a tool for appropriate treatment selection.

Takashi Yoshioka

Research Associate
Fukushima Medical University
Fukushima, Fukushima, Japan

Takashi Yoshioka, MD, MPH, PhD
Position: Research Associate, Fukushima Medical University
Affiliation: Center for Innovative Research for Communities and Clinical Excellence, Fukushima Medical University

Hideaki Hashimoto

Department of Urology, Okayama Central Hospital
Okayama, Okayama, Japan

Masaya Imoto

Department of Urology, Abiko Toho Hospital
Abiko, Chiba, Japan

Hiroshi Aoki

Department of Urology, Abiko Toho Hospital
Abiko, Chiba, Japan

Tomoya Yamasaki

Department of Urology, Abiko Toho Hospital
Abiko, Chiba, Japan

Hideo Otsuki

Department of Urology, Abiko Toho Hospital
Abiko, Chiba, Japan

Tatsushi Kawada

Department of Urology, Onomichi Municipal Hospital
Onomichi, Hiroshima, Japan

Tadashi Oeda

Department of Urology, Onomichi Municipal Hospital
Onomichi, Hiroshima, Japan

Noritaka Ishito

Department of Urology, Kurashiki Medical Center
Kurashiki, Okayama, Japan

Hitoshi Takamoto

Department of Urology, Kurashiki Medical Center
Kurashiki, Okayama, Japan

Hiroyuki Iio

Department of Urology, Matsuyama Shimin Hospital
Matsuyama, Ehime, Japan

Ryuta Watanabe

Department of Urology, Ehime University School of Medicine
Toon, Ehime, Japan

Tokuhiro Iseda

Department of Urology, Matsuyama Shimin Hospital
Matsuyama, Ehime, Japan

Takuya Sadahira

Clinical Fellow
Department of Urology; Okayama University Graduate School of Medicine; Okayama, Japan
Okayama, Okayama, Japan

Takuya Sadahira M.D.
2011-2013 Resident, Okayama University Hospital, Japan
2013-2016 Resident, Department of Urology, Okayama University Hospital, Japan
2016-present Clinical Fellow, Department of Urology, Okayama Medical Hospital, Japan

Koichiro Wada

assistant professor
Department of Urology; Okayama University Graduate School of Medicine; Okayama, Japan
Okayama, Okayama, Japan

Motoo Araki

Department of Urology; Okayama University Graduate School of Medicine; Okayama, Japan
Okayama, Okayama, Japan

Yoshiyuki Miyaji

Associate Professor
Department of Urology, Kawasaki Medical School, Kurashiki, Japan
Kurashiki, Okayama, Japan

Shinya Uehara

Department of Urology, Kawasaki Medical School General Medical Center
Okayama, Okayama, Japan

Takashi Saika

Professor and Chairman
Department of Urology, Ehime University School of Medicine,Toon,Japan
Toon, Ehime, Japan

Takashi Saika MD,PhD
Professor and Chair of Urology, Ehime University School of medicine.

Yasutomo Nasu

professor
Department of Urology; Okayama University Graduate School of Medicine; Okayama, Japan
Okayama, Okayama, Japan