The Impact of Dose Escalation on Secondary Cancer Risk After Radiotherapy of Prostate Cancer

2007 ◽  
Vol 68 (3) ◽  
pp. 892-897 ◽  
Author(s):  
Uwe Schneider ◽  
Antony Lomax ◽  
Jürgen Besserer ◽  
Peter Pemler ◽  
Norbert Lombriser ◽  
...  
2006 ◽  
Vol 78 ◽  
pp. S54
Author(s):  
U. Schneider ◽  
A. Lomax ◽  
J. Besserer ◽  
N. Lombriser ◽  
P. Pemler ◽  
...  

2020 ◽  
Vol 21 (9) ◽  
pp. 82-89
Author(s):  
Emel Haciislamoglu ◽  
Gorkem Gungor ◽  
Gokhan Aydin ◽  
Emine Canyilmaz ◽  
Ozan Cem Guler ◽  
...  

2009 ◽  
Vol 185 (4) ◽  
pp. 248-253 ◽  
Author(s):  
Judith Alvarez Moret ◽  
Oliver Koelbl ◽  
Ludwig Bogner

2017 ◽  
Vol 41 ◽  
pp. S15
Author(s):  
C.R. Vandevoorde ◽  
P. Beukes ◽  
X. Miles ◽  
E. de Kock ◽  
J. Symons ◽  
...  

2021 ◽  
Author(s):  
Antonio Bandala-Jacques ◽  
Kevin Daniel Castellanos Esquivel ◽  
Fernanda Pérez-Hurtado ◽  
Cristobal Hernández-Silva ◽  
Nancy Reynoso-Noverón

BACKGROUND Screening for prostate cancer has long been a debated, complex topic. The use of risk calculators for prostate cancer is recommended for determining patients’ individual risk of cancer and the subsequent need for a prostate biopsy. These tools could lead to a better discrimination of patients in need of invasive diagnostic procedures and for optimized allocation of healthcare resources OBJECTIVE To systematically review available literature on current prostate cancer risk calculators’ performance in healthy population, by comparing the impact factor of individual items on different cohorts, and the models’ overall performance. METHODS We performed a systematic review of available prostate cancer risk calculators targeted at healthy population. We included studies published from January 2000 to March 2021 in English, Spanish, French, Portuguese or German. Two reviewers independently decided for or against inclusion based on abstracts. A third reviewer intervened in case of disagreements. From the selected titles, we extracted information regarding the purpose of the manuscript, the analyzed calculators, the population for which it was calibrated, the included risk factors, and the model’s overall accuracy. RESULTS We included a total of 18 calculators across 53 different manuscripts. The most commonly analyzed ones were they PCPT and ERSPC risk calculators, developed from North American and European cohorts, respectively. Both calculators provided high precision for the diagnosis of aggressive prostate cancer (AUC as high as 0.798 for PCPT and 0.91 for ERSPC). We found 9 calculators developed from scratch for specific populations, which reached diagnostic precisions as high as 0.938. The most commonly included risk factors in the calculators were age, PSA levels and digital rectal examination findings. Additional calculators included race and detailed personal and family history CONCLUSIONS Both the PCPR and the ERSPC risk calculators have been successfully adapted for cohorts other than the ones they were originally created for with no loss of diagnostic accuracy. Furthermore, designing calculators from scratch considering each population’s sociocultural differences has resulted in risk tools that can be well adapted to be valid in more patients. The best risk calculator for prostate cancer will be that which was has been calibrated for its intended population and can be easily reproduced and implemented CLINICALTRIAL CRD42021242110


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