Inventory of prostate cancer predictive tools

Current Opinion in Urology

Volumn 18, Issue 3, 2008, Pages 279-296

  Shariat, Shahrokh F ^a,d   Karakiewicz, Pierre I ^b   Margulis, Vitaly ^a   Kattan, Michael W ^c  

^a UNIVERSITY OF TEXAS AT DALLAS   (United States)

^b UNIVERSITÉ DE MONTRÉAL   (Canada)

^c LERNER RESEARCH INSTITUTE   (United States)

^d UNIVERSITY OF TEXAS SOUTHWESTERN MEDICAL CENTER   (United States)

Author keywords

Nomogram; Prediction; Prostate cancer; Recurrence

Indexed keywords

ACCURACY; BRACHYTHERAPY; CANCER RECURRENCE; CANCER SURVIVAL; CLINICAL DECISION MAKING; EXTERNAL BEAM RADIOTHERAPY; HUMAN; LIFE EXPECTANCY; METASTASIS; NOMOGRAM; PREDICTION; PRIORITY JOURNAL; PROGNOSIS; PROSTATE BIOPSY; PROSTATE CANCER; PROSTATECTOMY; REVIEW; VALIDATION PROCESS;

BIOPSY; DIAGNOSTIC IMAGING; DISEASE PROGRESSION; EVIDENCE-BASED MEDICINE; HUMANS; LIFE EXPECTANCY; MALE; NEOPLASM METASTASIS; NEOPLASM STAGING; NOMOGRAMS; PREDICTIVE VALUE OF TESTS; PROBABILITY; PROSTATECTOMY; PROSTATIC NEOPLASMS; SURVIVAL ANALYSIS; TUMOR MARKERS, BIOLOGICAL;

EID: 41749085784     PISSN: 09630643     EISSN: None     Source Type: Journal    
DOI: 10.1097/MOU.0b013e3282f9b3e5     Document Type: Review

References (140)

1. Jemal A, Siegel R, Ward E, et al. Cancer statistics, 2007. CA Cancer J Clin 2007; 57:43-66.
2. Elstein AS. Heuristics and biases: selected errors in clinical reasoning. Acad Med 1999; 74:791-794.
3. Vlaev I, Chater N. Game relativity: how context influences strategic decision making. J Exp Psychol Learn Mem Cogn 2006; 32:131-149.
4. Kattan M. Expert systems in medicine. In: Smelser NJ, Baltes PB, editors. International encyclopedia of the social and behavioral sciences. Oxford: Pergamon; 2001. p. 5135.
5. Hogarth RM, Karelaia N. Heuristic and linear models of judgment: matching rules and environments. Psychol Rev 2007; 114:733-758.
6. Ross PL, Scardino PT, Kattan MW. A catalog of prostate cancer nomograms. J Urol 2001; 165:1562-1568.
7. Babaian RJ, Fritsche HA, Zhang Z, et al. Evaluation of prostAsure index in the detection of prostate cancer: a preliminary report. Urology 1998; 51:132-136.
8. Eastham JA, May R, Robertson JL, et al. Development of a nomogram that predicts the probability of a positive prostate biopsy in men with an abnormal digital rectal examination and a prostate-specific antigen between 0 and 4 ng/mL. Urology 1999; 54:709-713.
9. Virtanen A, Gomari M, Kranse R, Stenman UH. Estimation of prostate cancer probability by logistic regression: free and total prostate-specific antigen, digital rectal examination, and heredity are significant variables. Clin Chem 1999; 45:987-994.
10. Finne P, Finne R, Auvinen A, et al. Predicting the outcome of prostate biopsy in screen-positive men by a multilayer perceptron network. Urology 2000; 56:418-422.
11. Horninger W, Bartsch G, Snow PB, et al. The problem of cutoff levels in a screened population: appropriateness of informing screenees about their risk of having prostate carcinoma. Cancer 2001; 91:1667-1772.
12. Kalra P, Togami J, Bansal BSG, et al. A neurocomputational model for prostate carcinoma detection. Cancer 2003; 98:1849-1854.
13. Garzotto M, Hudson RG, Peters L, et al. Predictive modeling for the presence of prostate carcinoma using clinical, laboratory, and ultrasound parameters in patients with prostate specific antigen levels < or = 10 ng/mL. Cancer 2003; 98:1417-1422.
14. Finne P, Finne R, Bangma C, et al. Algorithms based on prostate-specific antigen (PSA), free PSA, digital rectal examination and prostate volume reduce false-positive PSA results in prostate cancer screening. Int J Cancer 2004; 111:310-315.
15. Karakiewicz PI, Benayoun S, Kattan MW, et al. Development and validation of a nomogram predicting the outcome of prostate biopsy based on patient age, digital rectal examination and serum prostate specific antigen. J Urol 2005; 173:1930-1934.
16. Suzuki H, Komiya A, Kamiya N, et al. Development of a nomogram to predict probability of positive initial prostate biopsy among Japanese patients. Urology 2006; 67:131-136.
17. Chun FK, Briganti A, Graefen M, et al. Development and external validation of an extended 10-core biopsy nomogram. Eur Urol 2007; 52:436-444. Chun et al. demonstrate that nomograms developed in the sextant biopsy era may not be able to predict the probability of prostate cancer on needle biopsy in the extended biopsy era, equally accurate as they used to in the sextant biopsy era. Therefore, the authors developed and internally validated an extended biopsy nomogram.
18. Porter CR, Gamito EJ, Crawford ED, et al. Model to predict prostate biopsy outcome in large screening population with independent validation in referral setting. Urology 2005; 65:937-941.
19. Chun FK, Briganti A, Graefen M, et al. Development and external validation of an extended repeat biopsy nomogram. J Urol 2007; 177:510-515.
20. O'Dowd GJ, Miller MC, Orozco R, Veltri RW. Analysis of repeated biopsy results within 1 year after a noncancer diagnosis. Urology 2000; 55:553-559.
21. Lopez-Corona E, Ohori M, Scardino PT, et al. A nomogram for predicting a positive repeat prostate biopsy in patients with a previous negative biopsy session. J Urol 2003; 170:1184-1188.
22. Remzi M, Anagnostou T, Ravery V, et al. An artificial neural network to predict the outcome of repeat prostate biopsies. Urology 2003; 62:456-460.
23. Yanke BV, Gonen M, Scardino PT, Kattan MW. Validation of a nomogram for predicting positive repeat biopsy for prostate cancer. J Urol 2005; 173:421-424.
24. Walz J, Graefen M, Chun FK, et al. High incidence of prostate cancer detected by saturation biopsy after previous negative biopsy series. Eur Urol 2006; 50:498-505.
25. Snow PB, Smith DS, Catalona WJ. Artificial neural networks in the diagnosis and prognosis of prostate cancer: a pilot study. J Urol 1994; 152:1923-1926.
26. Carlson GD, Calvanese CB, Partin AW. An algorithm combining age, total prostate-specific antigen (PSA), and percentage free PSA to predict prostate cancer: results on 4298 cases. Urology 1998; 52:455-461.
27. Djavan B, Remzi M, Zlotta A, et al. Novel artificial neural network for early detection of prostate cancer. J Clin Oncol 2002; 20:921-929.
28. Stephan C, Cammann H, Semjonow A, et al. Multicenter evaluation of an artificial neural network to increase the prostate cancer detection rate and reduce unnecessary biopsies. Clin Chem 2002; 48:1279-1287.
29. Porter CR, O'Donnell C, Crawford ED, et al. Predicting the outcome of prostate biopsy in a racially diverse population: a prospective study. Urology 2002; 60:831-835.
30. Matsui Y, Utsunomiya N, Ichioka K, et al. The use of artificial neural network analysis to improve the predictive accuracy of prostate biopsy in the Japanese population. Jpn J Clin Oncol 2004; 34:602-607.
31. Benecchi L. Neuro-fuzzy system for prostate cancer diagnosis. Urology 2006; 68:357-361.
32. Yanke BV, Carver BS, Bianco FJ Jr, et al. African-American race is a predictor of prostate cancer detection: incorporation into a prebiopsy nomogram. BJU Int 2006; 98:783-787.
33. Narayan P, Gajendran V, Taylor SP, et al. The role of transrectal ultrasound-guided biopsy-based staging, preoperative serum prostate-specific antigen, and biopsy Gleason score in prediction of final pathologic diagnosis in prostate cancer. Urology 1995; 46:205-212.
34. Partin AW, Yoo J, Carter HB, et al. The use of prostate specific antigen, clinical stage and Gleason score to predict pathological stage in men with localized prostate cancer. J Urol 1993; 150:110-114.
35. Kattan MW, Stapleton AM, Wheeler TM, Scardino PT. Evaluation of a nomogram used to predict the pathologic stage of clinically localized prostate carcinoma. Cancer 1997; 79:528-537.
36. Partin AW, Mangold LA, Lamm DM, et al. Contemporary update of prostate cancer staging nomograms (Partin tables) for the new millennium. Urology 2001; 58:843-848.
37. Makarov DV, Trock BJ, Humphreys EB, et al. Updated nomogram to predict pathologic stage of prostate cancer given prostate-specific antigen level, clinical stage, and biopsy Gleason score (Partin tables) based on cases from 2000 to 2005. Urology 2007; 69:1095-1101. The authors have updated the 'Partin tables' on the basis of data from men treated after 2000, to reflect current trends in presentation and pathologic stage in men newly diagnosed with PCa. Clinicians can use these nomograms, based on the large cohort of men with PCA treated at John Hopkins University, to counsel individual patients and help them make important management decisions.
38. Partin AW, Kattan MW, Subong EN, et al. Combination of prostate-specific antigen, clinical stage, and Gleason score to predict pathological stage of localized prostate cancer: a multiinstitutional update. JAMA 1997; 277:1445-1451 [erratum 1997; 278:118].
39. Blute ML, Bergstralh EJ, Partin AW, et al. Validation of Partin tables for predicting pathological stage of clinically localized prostate cancer. J Urol 2000; 164:1591-1595.
40. Epstein JI, Walsh PC, Carmichael M, Brendler CB. Pathologic and clinical findings to predict tumor extent of nonpalpable (stage T1c) prostate cancer. JAMA 1994; 271:368-374.
41. Carter HB, Epstein JI. Prediction of significant cancer in men with stage T1c adenocarcinoma of the prostate. World J Urol 1997; 15:359-363.
42. Goto Y, Ohori M, Arakawa A, et al. Distinguishing clinically important from unimportant prostate cancers before treatment: value of systematic biopsies. J Urol 1996; 156:1059-1063.
43. Kattan MW, Eastham JA, Wheeler TM, et al. Counseling men with prostate cancer: a nomogram for predicting the presence of small, moderately differentiated, confined tumors. J Urol 2003; 170:1792-1797.
44. Steyerberg EW, Roobol MJ, Kattan MW, et al. Prediction of indolent prostate cancer: validation and updating of a prognostic nomogram. J Urol 2007; 177:107-112. Based on substantial difference in the prevalence of clinically insignificant prostate cancer between referral and screening populations, Steyerberg et al. updated previous nomograms for screened patients. These nomograms show that clinically insignificant prostate cancer can be predicted with reasonable accuracy, which may help in the decision-making process between definitive therapy and active surveillance.
45. Chun FK, Steuber T, Erbersdobler A, et al. Development and internal validation of a nomogram predicting the probability of prostate cancer Gleason sum upgrading between biopsy and radical prostatectomy pathology. Eur Urol 2006; 49:820-826.
46. Chun FK, Briganti A, Shariat SF, et al. Significant upgrading affects a third of men diagnosed with prostate cancer: predictive nomogram and internal validation. BJU Int 2006; 98:329-334.
47. Steuber T, Chun FK, Erbersdobler A, et al. Development and internal validation of preoperative transition zone prostate cancer nomogram. Urology 2006; 68:1295-1300.
48. Peller PA, Young DC, Marmaduke DP, et al. Sextant prostate biopsies: a histopathologic correlation with radical prostatectomy specimens. Cancer 1995; 75:530-538.
49. Ackerman DA, Barry JM, Wicklund RA, et al. Analysis of risk factors associated with prostate cancer extension to the surgical margin and pelvic node metastasis at radical prostatectomy. J Urol 1993; 150:1845-1850.
50. Rabbani F, Bastar A, Fair WR. Site specific predictors of positive margins at radical prostatectomy: an argument for risk based modification of technique. J Urol 1998; 160:1727-1733.
51. Bostwick DG, Qian J, Bergstralh E, et al. Prediction of capsular perforation and seminal vesicle invasion in prostate cancer. J Urol 1996; 155:1361-1367.
52. Gamito EJ, Stone NN, Batuello JT, Crawford ED. Use of artificial neural networks in the clinical staging of prostate cancer: implications for prostate brachytherapy. Tech Urol 2000; 6:60-63.
53. Gilliland FD, Hoffman RM, Hamilton A, et al. Predicting extracapsular extension of prostate cancer in men treated with radical prostatectomy: results from the population based prostate cancer outcomes study. J Urol 1999; 162:1341-1345.
54. Ohori M, Kattan MW, Koh H, et al. Predicting the presence and side of extracapsular extension: a nomogram for staging prostate cancer. J Urol 2004; 171:1844-1849.
55. Steuber T, Graefen M, Haese A, et al. Validation of a nomogram for prediction of side specific extracapsular extension at radical prostatectomy. J Urol 2006; 175:939-944.
56. Badalament RA, Miller MC, Peller PA, et al. An algorithm for predicting nonorgan confined prostate cancer using the results obtained from sextant core biopsies with prostate specific antigen level. J Urol 1996; 156:1375-1380.
57. Pisansky TM, Blute ML, Suman VJ, et al. Correlation of pretherapy prostate cancer characteristics with seminal vesicle invasion in radical prostatectomy specimens. Int J Radiat Oncol Biol Phys 1996; 36:585-591.
58. Koh H, Kattan MW, Scardino PT, et al. A nomogram to predict seminal vesicle invasion by the extent and location of cancer in systematic biopsy results. J Urol 2003; 170:1203-1208.
59. Baccala A Jr, Reuther AM, Bianco FJ Jr, et al. Complete resection of seminal vesicles at radical prostatectomy results in substantial long-termdisease-free survival: multiinstitutional study of 6740 patients. Urology 2007; 69:536-540.
60. Gallina A, Chu n FK, Briganti A, et al. Development and split-sample validation of a nomogram predicting the probability of seminal vesicle invasion at radical prostatectomy. Eur Urol 2007; 52:98-105.
61. Bluestein DL, Bostwick DG, Bergstralh EJ, Oesterling JE. Eliminating the need for bilateral pelvic lymphadenectomy in select patients with prostate cancer. J Urol 1994; 151:1315-1320.
62. Batuello JT, Gamito EJ, Crawford ED, et al. Artificial neural network model for the assessment of lymph node spread in patients with clinically localized prostate cancer. Urology 2001; 57:481-485.
63. Roach M 3rd, Marquez C, Yuo HS, et al. Predicting the risk of lymph node involvement using the pretreatment prostate specific antigen and Gleason score in men with clinically localized prostate cancer. Int J Radiat Oncol Biol Phys 1994; 28:33-37.
64. Cagiannos I, Karakiewicz P, Eastham JA, et al. A preoperative nomogram identifying decreased risk of positive pelvic lymph nodes in patients with prostate cancer. J Urol 2003; 170:1798-1803.
65. Briganti A, Chun FK, Salonia A, et al. Validation of a nomogram predicting the probability of lymph node invasion based on the extent of pelvic lymphadenectomy in patients with clinically localized prostate cancer. BJU Int 2006; 98:788-793.
66. Briganti A, Chun FK, Salonia A, et al. Validation of a nomogram predicting the probability of lymph node invasion among patients undergoing radical prostatectomy and an extended pelvic lymphadenectomy. Eur Urol 2006; 49:1019-1026.
67. Briganti A, Karakiewicz PI, Chun FK, et al. Percentage of positive biopsy cores can improve the ability to predict lymph node invasion in patients undergoing radical prostatectomy and extended pelvic lymph node dissection. Eur Urol 2007; 51:1573-1581.
68. Graefen M, Haese A, Pichlmeier U, et al. A validated strategy for side specific prediction of organ confined prostate cancer: a tool to select for nerve sparing radical prostatectomy. J Urol 2001; 165:857-863.
69. Augustin H, Eggert T, Wenske S, et al. Comparison of accuracy between the Partin tables of 1997 and 2001 to predict final pathological stage in clinically localized prostate cancer. J Urol 2004; 171:177-181.
70. Heidenreich A, Varga Z, Von Knobloch R. Extended pelvic lymphadenectomy in patients undergoing radical prostatectomy: high incidence of lymph node metastasis. J Urol 2002; 167:1681-1686.
71. Bader P, Burkhard FC, Markwalder R, Studer UE. Is a limited lymph node dissection an adequate staging procedure for prostate cancer? J Urol 2002; 168:514-518.
72. Briganti A, Chun FK, Salonia A, et al. A nomogram for staging of exclusive nonobturator lymph node metastases in men with localized prostate cancer. Eur Urol 2007; 51:112-119.
73. Johansson JE, Andren O, Andersson SO, et al. Natural history of early, localized prostate cancer. JAMA 2004; 291:2713-2719.
74. Epstein JI, Carmichael MJ, Partin AW, Walsh PC. Small high grade adenocarcinoma of the prostate in radical prostatectomy specimens performed for nonpalpable disease: pathogenetic and clinical implications. J Urol 1994; 151:1587-1592.
75. D'Amico AV, Whittington R, Malkowicz SB, et al. Pretreatment nomogram for prostate-specific antigen recurrence after radical prostatectomy or external-beam radiation therapy for clinically localized prostate cancer. J Clin Oncol 1999; 17:168-172.
76. D'Amico AV, Whittington R, Malkowicz SB, et al. Combination of the preoperative PSA level, biopsy Gleason score, percentage of positive biopsies, and MRI T-stage to predict early PSA failure in men with clinically localized prostate cancer. Urology 2000; 55:572-577.
77. Graefen M, Noldus J, Pichlmeier U, et al. Early prostate-specific antigen relapse after radical retropubic prostatectomy: prediction on the basis of preoperative and postoperative tumor characteristics. Eur Urol 1999; 36: 21-30.
78. D'Amico AV, Keshaviah A, Manola J, et al. Clinical utility of the percentage of positive prostate biopsies in predicting prostate cancer-specific and overall survival after radiotherapy for patients with localized prostate cancer. Int J Radiat Oncol Biol Phys 2002; 53:581-587.
79. D'Amico AV, Whittington R, Malkowicz SB, et al. The combination of preoperative prostate specific antigen and postoperative pathological findings to predict prostate specific antigen outcome in clinically localized prostate cancer. J Urol 1998; 160:2096-2101.
80. Mitchell JA, Cooperberg MR, Elkin EP, et al. Ability of 2 pretreatment risk assessment methods to predict prostate cancer recurrence after radical prostatectomy: data from CaPSURE. J Urol 2005; 173:1126-1131.
81. Graefen M, Karakiewicz PI, Cagiannos I, et al. A validation of two preoperative nomograms predicting recurrence following radical prostatectomy in a cohort of European men. Urol Oncol 2002; 7:141-146.
82. Kattan MW, Eastham JA, Stapleton AM, et al. A preoperative nomogram for disease recurrence following radical prostatectomy for prostate cancer. J Natl Cancer Inst 1998; 90:766-771.
83. Greene KL, Meng MV, Elkin EP, et al. Validation of the Kattan preoperative nomogram for prostate cancer recurrence using a community based cohort: results from cancer of the prostate strategic urological research endeavor (capsure). J Urol 2004; 171:2255-2259.
84. Graefen M, Augustin H, Karakiewicz PI, et al. Can nomograms derived in the U.S. applied to German patients? A study about the validation of preoperative nomograms predicting the risk of recurrence after radical prostatectomy. Urologe A 2003; 42:685-692.
85. Graefen M, Karakiewicz PI, Cagiannos I, et al. International validation of a preoperative nomogram for prostate cancer recurrence after radical prostatectomy. J Clin Oncol 2002; 20:3206-3212.
86. Stephenson AJ, Scardino PT, Eastham JA, et al. Preoperative nomogram predicting the 10-year probability of prostate cancer recurrence after radical prostatectomy. J Natl Cancer Inst 2006; 98:715-717. Stephenson et al. report on salvage radiotherapy outcomes in a multiinstitutional cohort of 1540 patients treated for biochemical recurrence after radical prostatectomy. An overall 6-year progression-free probability of 32% was found. PSA level at the time of salvage therapy, PSA doubling times using a cutoff of 10 months, and prostatectomy Gleason score of 8-10 emerged as strong predictive factors. This study confirms the high success rate with early initiation of salvage radiotherapy; demonstrates the durability of salvage responses; and offers a nomogram that should prove useful in providing recommendations to patients. The implications of these findings are that many PSA failures, at least early in their course, are still local in nature and that the sensitivity of the PSA assay, when followed and acted on diligently, may temper the need for a purely adjuvant approach.
87. Cooperberg MR, Pasta DJ, Elkin EP, et al. The University of California, San Francisco Cancer of the Prostate Risk Assessment score: a straightforward and reliable preoperative predictor of disease recurrence after radical prostatectomy. J Urol 2005; 173:1938-1942.
88. Cooperberg MR, Freedland SJ, Pasta DJ, et al. Multiinstitutional validation of the UCSF cancer of the prostate risk assessment for prediction of recurrence after radical prostatectomy. Cancer 2006; 107:2384-2391.
89. Tewari A, Issa M, El-Galley R, et al. Genetic adaptive neural network to predict biochemical failure after radical prostatectomy: a multiinstitutional study. Mol Urol 2001; 5:163-169.
90. Bauer JJ, Connelly RR, Seterhenn IA, et al. Biostatistical modeling using traditional preoperative and pathological prognostic variables in the selection of men at high risk for disease recurrence after radical prostatectomy for prostate cancer. J Urol 1998; 159:929-933.
91. Moul JW, Connelly RR, Lubeck DP, et al. Predicting risk of prostate specific antigen recurrence after radical prostatectomy with the Center for Prostate Disease Research and Cancer of the Prostate Strategic Urologic Research Endeavor databases. J Urol 2001; 166:1322-1327.
92. Stamey TA, Yemoto CM, McNeal JE, et al. Prostate cancer is highly predictable: a prognostic equation based on all morphological variables in radical prostatectomy specimens. J Urol 2000; 163:1155-1160.
93. McAleer SJ, Schultz D, Whittington R, et al. PSA outcome following radical prostatectomy for patients with localized prostate cancer stratified by prostatectomy findings and the preoperative PSA level. Urol Oncol 2005; 23:311-317.
94. Potter SR, Miller MC, Mangold LA, et al. Genetically engineered neural networks for predicting prostate cancer progression after radical prostatectomy. Urology 1999; 54:791-795.
95. Kattan MW, Wheeler TM, Scardino PT. Postoperative nomogram for disease recurrence after radical prostatectomy for prostate cancer. J Clin Oncol 1999; 17:1499-1507.
96. Graefen M, Karakiewicz PI, Cagiannos I, et al. Validation study of the accuracy of a postoperative nomogram for recurrence after radical prostatectomy for localized prostate cancer. J Clin Oncol 2002; 20:951-956.
97. Ramsden AR, Chodak G. An analysis of risk factors for biochemical progression in patients with seminal vesicle invasion: validation of Kattan's nomogram in a pathological subgroup. BJU Int 2004; 93:961-964.
98. Bianco FJ Jr, Kattan MW, Scardino PT, et al. Radical prostatectomy nomograms in black American men: accuracy and applicability. J Urol 2003; 170:73-76.
99. Stephenson AJ, Scardino PT, Eastham JA, et al. Postoperative nomogram predicting the 10-year probability of prostate cancer recurrence after radical prostatectomy. J Clin Oncol 2005; 23:7005-7012.
100. Hull GW, Rabbani F, Abbas F, et al. Cancer control with radical prostatectomy alone in 1,000 consecutive patients. J Urol 2002; 167:528-534.
101. Pound CR, Partin AW, Eisenberger MA, et al. Natural history of progression after PSA elevation following radical prostatectomy. JAMA 1999; 281:1591-1597.
102. Freedland SJ, Humphreys EB, Mangold LA, et al. Risk of prostate cancer-specific mortality following biochemical recurrence after radical prostatectomy. JAMA 2005; 294:433-439.
103. Cagiannos I, Karakiewicz P, Graefen M, et al. Is year of radical prostatectomy a predictor of outcome in prostate cancer? J Urol 2004; 171:692-696.
104. Duchesne GM, Bloomfield D, Wall P. Identification of intermediate-risk prostate cancer patients treated with radiotherapy suitable for neoadjuvant hormone studies. Radiother Oncol 1996; 38:7-12.
105. Pisansky TM, Kahn MJ, Bostwick DG. An enhanced prognostic system for clinically localized carcinoma of the prostate. Cancer 1997; 79:2154-2161.
106. Zagars GK, Pollack A, von Eschenbach AC. Prognostic factors for clinically localized prostate carcinoma: analysis of 938 patients irradiated in the prostate specific antigen era. Cancer 1997; 79:1370-1380.
107. Shipley WU, Thames HD, Sandler HM, et al. Radiation therapy for clinically localized prostate cancer: a multiinstitutional pooled analysis. JAMA 1999; 281:1598-1604.
108. Kattan MW, Zelefsky MJ, Kupelian PA, et al. Pretreatment nomogram for predicting the outcome of three-dimensional conformal radiotherapy in prostate cancer. J Clin Oncol 2000; 18:3352-3359.
109. Potters L, Morgenstern C, Calugaru E, et al. 12-year outcomes following permanent prostate brachytherapy in patients with clinically localized prostate cancer. J Urol 2005; 173:1562-1566.
110. D'Amico AV, Whittington R, Malkowicz SB, et al. Biochemical outcome after radical prostatectomy or external beam radiation therapy for patients with clinically localized prostate carcinoma in the prostate specific antigen era. Cancer 2002; 95:281-286.
111. D'Amico AV, Whittington R, Malkowicz SB, et al. Biochemical outcome after radical prostatectomy, external beam radiation therapy, or interstitial radiation therapy for clinically localized prostate cancer. JAMA 1998; 280:969-974.
112. Ragde H, Elgamal AA, Snow PB, et al. Ten-year disease free survival after transperineal sonography-guided iodine-125 brachytherapy with or without 45-gray external beam irradiation in the treatment of patients with clinically localized, low to high Gleason grade prostate carcinoma. Cancer 1998; 83:989-1001.
113. Kattan MW, Potters L, Blasko JC, et al. Pretreatment nomogram for predicting freedom from recurrence after permanent prostate brachytherapy in prostate cancer. Urology 2001; 58:393-399.
114. Partin AW, Pearson JD, Landis PK, et al. Evaluation of serum prostate-specific antigen velocity after radical prostatectomy to distinguish local recurrence from distant metastases. Urology 1994; 43:649-659.
115. D'Amico AV, Moul J, Carroll PR, et al. Cancer-specific mortality after surgery or radiation for patients with clinically localized prostate cancer managed during the prostate-specific antigen era. J Clin Oncol 2003; 21:2163-2172.
116. Dotan ZA, Bianco FJ Jr, Rabbani F, et al. Pattern of prostate-specific antigen (PSA) failure dictates the probability of a positive bone scan in patients with an increasing PSA after radical prostatectomy. J Clin Oncol 2005; 23:1962-1968.
117. D'Amico AV, Cote K, Loffredo M, et al. Determinants of prostate cancer-specific survival after radiation therapy for patients with clinically localized prostate cancer. J Clin Oncol 2002; 20:4567-4573.
118. D'Amico AV, Cote K, Loffredo M, et al. Determinants of prostate cancer specific survival following radiation therapy during the prostate specific antigen era. J Urol 2003; 170:S42-S46.
119. Kattan MW, Zelefsky MJ, Kupelian PA, et al. Pretreatment nomogram that predicts 5-year probability of metastasis following three-dimensional conformal radiation therapy for localized prostate cancer. J Clin Oncol 2003; 21:4568-4571.
120. Slovin SF, Wilton AS, Heller G, Scher HI. Time to detectable metastatic disease in patients with rising prostate-specific antigen values following surgery or radiation therapy. Clin Cancer Res 2005; 11:8669-8673.
121. Zhou P, Chen MH, McLeod D, et al. Predictors of prostate cancer-specific mortality after radical prostatectomy or radiation therapy. J Clin Oncol 2005; 23:6992-6998.
122. Stephenson AJ, Scardino PT, Kattan MW, et al. Predicting the outcome of salvage radiation therapy for recurrent prostate cancer after radical prostatectomy. J Clin Oncol 2007; 25:2035-2041.
123. Svatek R, Karakiewicz PI, Shulman M, et al. Pretreatment nomogram for disease-specific survival of patients with chemotherapy-naive androgen independent prostate cancer. Eur Urol 2006; 49:666-674.
124. Smaletz O, Scher HI, Small EJ, et al. Nomogram for overall survival of patients with progressive metastatic prostate cancer after castration. J Clin Oncol 2002; 20:3972-3982.
125. Porter CR, Gallina A, Kodama K, et al. Prostate cancer-specific survival in men treated with hormonal therapy after failure of radical prostatectomy. Eur Urol 2007; 52:446-452.
126. Halabi S, Small EJ, Kantoff PW, et al. Prognostic model for predicting survival in men with hormone-refractory metastatic prostate cancer. J Clin Oncol 2003; 21:1232-1237.
127. Tewari A, Johnson CC, Divine G, et al. Long-term survival probability in men with clinically localized prostate cancer: a case-control, propensity modeling study stratified by race, age, treatment and comorbidities. J Urol 2004; 171:1513-1519.
128. Albertsen PC, Fryback DG, Storer BE, et al. The impact of co-morbidity on life expectancy among men with localized prostate cancer. J Urol 1996; 156:127-132.
129. Cowen ME, Halasyamani LK, Kattan MW. Predicting life expectancy in men with clinically localized prostate cancer. J Urol 2006; 175:99-103.
130. Albertsen PC, Hanley JA, Gleason DF, Barry MJ. Competing risk analysis of men aged 55 to 74 years at diagnosis managed conservatively for clinically localized prostate cancer. JAMA 1998; 280:975-980.
131. Walz J, Gallina A, Saad F, et al. A nomogram predicting 10-year life expectancy in candidates for radical prostatectomy or radiotherapy for prostate cancer. J Clin Oncol 2007; 25:3576-3581. The investigators developed a nomogram predictive of survival, which includes age, Charlson Comorbidity Index, and type of local therapy planned (radiation or surgery), and demonstrated an 85% accuracy in their split-sample validation cohort. This nomogram is relevant to clinicians who take care of patients with localized PCa, where there is accumulating evidence that many patients with low-risk features are overtreated. This nomogram is most, if not exclusively, relevant to patients who present with low-risk localized disease. It would have been useful if the authors had examined in detail the attributable risk for outcome based on the local therapy choice. This nomogram is only validated with an internal sample, although it was compared with (and found superior to) another similar model.
132. Wang L, Hricak H, Kattan MW, et al. Combined endorectal and phased-array MRI in the prediction of pelvic lymph node metastasis in prostate cancer. AJR Am J Roentgenol 2006; 186:743-748.
133. Wang L, Hricak H, Kattan MW, et al. Prediction of seminal vesicle invasion in prostate cancer: incremental value of adding endorectal MR imaging to the Kattan nomogram. Radiology 2007; 242:182-188. Wang and colleagues suggest that technological advances in MRI, as well as urologists' and radiologists' increased experience with prostate MRI, have contributed to its increased value in the preoperative evaluation of men with prostate cancer.
134. Shukla-Dave A, Hricak H, Kattan MW, et al. The utility of magnetic resonance imaging and spectroscopy for predicting insignificant prostate cancer: an initial analysis. BJU Int 2007; 99:786-793.
135. Kattan MW, Shariat SF, Andrews B, et al. The addition of interleukin-6 soluble receptor and transforming growth factor beta1 improves a preoperative nomogram for predicting biochemical progression in patients with clinically localized prostate cancer. J Clin Oncol 2003; 21:3573-3579.
136. Stephenson AJ, Smith A, Kattan MW, et al. Integration of gene expression profiling and clinical variables to predict prostate carcinoma recurrence after radical prostatectomy. Cancer 2005; 104:290-298.
137. Hricak H, Choyke PL, Eberhardt SC, et al. Imaging prostate cancer: a multidisciplinary perspective. Radiology 2007; 243:28-53. Comprehensive excellent review article.
138. Hricak H, Wang L, Wei DC, et al. The role of preoperative endorectal magnetic resonance imaging in the decision regarding whether to preserve or resect neurovascular bundles during radical retropubic prostatectomy. Cancer 2004; 100:2655-2663.
139. Zakian KL, Sircar K, Hricak H, et al. Correlation of proton MR spectroscopic imaging with gleason score based on step-section pathologic analysis after radical prostatectomy. Radiology 2005; 234:804-814.
140. Poulakis V, Witzsch U, de Vries R, et al. Preoperative neural network using combined magnetic resonance imaging variables, prostate-specific antigen, and Gleason score for predicting prostate cancer biochemical recurrence after radical prostatectomy. Urology 2004; 64:1165-1170.