[go: up one dir, main page]

WO2007067672A2 - Procede de prediction de progression systemique chez des patients atteints de cancer de la prostate - Google Patents

Procede de prediction de progression systemique chez des patients atteints de cancer de la prostate Download PDF

Info

Publication number
WO2007067672A2
WO2007067672A2 PCT/US2006/046643 US2006046643W WO2007067672A2 WO 2007067672 A2 WO2007067672 A2 WO 2007067672A2 US 2006046643 W US2006046643 W US 2006046643W WO 2007067672 A2 WO2007067672 A2 WO 2007067672A2
Authority
WO
WIPO (PCT)
Prior art keywords
patient
factors
psadt
absence
psabcr
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/US2006/046643
Other languages
English (en)
Other versions
WO2007067672A3 (fr
Inventor
Michael Kattan
Kevin M. Slawin
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Baylor College of Medicine
Memorial Sloan Kettering Cancer Center
Original Assignee
Baylor College of Medicine
Memorial Sloan Kettering Cancer Center
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Baylor College of Medicine, Memorial Sloan Kettering Cancer Center filed Critical Baylor College of Medicine
Publication of WO2007067672A2 publication Critical patent/WO2007067672A2/fr
Publication of WO2007067672A3 publication Critical patent/WO2007067672A3/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06G—ANALOGUE COMPUTERS
    • G06G1/00—Hand manipulated computing devices
    • G06G1/0005—Hand manipulated computing devices characterised by a specific application
    • G06G1/001—Hand manipulated computing devices characterised by a specific application for medical purposes, for biological purposes

Definitions

  • Prostate cancer is the most commonly diagnosed cancer and the second leading cause of cancer death for men in the United States. In 1999, an estimated 179.300 men were diagnosed with prostate cancer and 37,000 died of this disease. Despite the identification of several new potential biomarkers for prostate cancer (e.g., p53, p21, p27, and E-cadherin), prostate specific antigen (PSA) and the histologic Gleason score have remained the most commonly used predictors of prostate cancer biology. In fact, the widespread use of PSA-based screening has dramatically increased the number of men diagnosed and treated for clinically localized prostate cancer over the past decade. Concomitantly, the incidence of clinical metastatic disease at the time of initial diagnosis has dropped considerably, in concert with an overall decrease in prostate cancer mortality (Merill et al., 2000).
  • PSA prostate specific antigen
  • Radical prostatectomy (RP) for clinically localized prostate cancer provides excellent cancer control and was recently shown to improve disease- specific survival when compared with surveillance (Holmberg et al., 2002; Hull et al., 2002; Han et al., 2001). Nevertheless, biochemical progression (BCR), manifested by increasing prostate-specific antigen (PSA), occurs in 15% to 40% of patients within 10 years after RP (Dillioglugil et al., 1997; Han et al., 2003; Roberts et al., 2001). Distant clinical progression after RP almost never develops without increasing PSA levels (Pound et al., 1999). The optimal means of evaluating patients with increasing serum PSA after RP has not been determined. However, it is clear that imaging should not be used for patients without elevated PSA levels after RP (Ferguson et al., 1995; Nudell et al., 2000).
  • Predictors for metastases may include preoperative variables, radical prostatectomy pathology variables, and characteristics of PSA failure.
  • risk factors for systemic progression following RP include pathology Gleason score, the interval from surgery to biochemical failure, and PSADT, while D'Amico et al. (2002; 2004) disclose that PSA doubling time is a surrogate end point for prostate cancer specific mortality after RP or radiation therapy.
  • the invention provides methods, apparatus and nomograms to predict the probability of freedom from metastases progression in patients with rising PSA after RP. Based on data available shortly after biochemical failure, the significant predictors for metastases progression among patients with rising PSA after RP were determined and a nomogram was prepared that predicts the probability of metastases progression among patients biochemical recurrence (BCR) after RP.
  • BCR biochemical recurrence
  • the invention provides a nomogram for the graphic representation of a quantitative probability of freedom from metastases progression in a prostate cancer patient with BCR after RP.
  • the nomogram includes a plurality of scales and a solid support, the plurality of scales being disposed on the support and comprising a scale for one or more, e.g., two, three, four, five or more patient factors, a points scale, a total points scale and a predictor scale.
  • the factors may include one or more of prostate specific antigen (PSA) doubling time (PSADT) 5 PSA level at BCR (PSABCR), Gleason score (GS), the presence or absence of seminal vesicle invasion (SVI), preRP PSA level, and/or the absence or extent of extracapular extension (ECE).
  • PSA prostate specific antigen
  • PSADT prostate specific antigen doubling time
  • GS Gleason score
  • VI seminal vesicle invasion
  • preRP PSA level preRP PSA level
  • ECE extracapular extension
  • the scales for PSADT, PSABCR, GS, SVI, preRP PSA level, and/or ECE each has values on the scales, wherein the scales for PSADT, PSABCR, GS, SVI, preRP PSA level, and/or ECE, are disposed on the solid support with respect to the points scale so that each of the values for PSADT, PSABCR, GS, SVI, preRP PSA level, and/or ECE, can be correlated with values on the points scale.
  • the total points scale has values on the total points scale and is disposed on the solid support with respect to the predictor scale so that the values on the total points scale may be correlated with values on the predictor scale, such that the values on the points scale correlating with the patient's PSADT, PSABCR, GS, presence or absence of SVI, preRP PSA level, and/or the absence or extent of ECE, can be added together to yield a total points value.
  • the total points value can then be correlated with the predictor scale to predict the quantitative probability of freedom from metastases progression in a prostate cancer patient with BCR after RP.
  • a method of using the nomogram is also provided.
  • the nomogram includes a plurality of scales, a solid support, a points scale, a total points scale and a predictor scale.
  • the plurality of scales are disposed on the support and include a scale for at least one, two, three, four, five or more patient factors, factors including PSADT, PSABCR, GS, the presence or absence of SVI, preRP PSA level, and/or the absence or extent of ECE.
  • the scales for PSADT, PSABCR, GS, SVI, preRP PSA level, and/or ECE each has values on the scales, and the scales for PSADT, PSABCR, GS, SVI, preRP PSA level, and/or ECE, are disposed on the solid support with respect to the points scale so that each of the values for PSADT, PSABCR, GS, SVI, preRP PSA level, and/or ECE, can be correlated with values on the points scale.
  • the total points scale has values on the total points scale and is disposed on the solid support with respect to the predictor scale so that the values on the total points scale may be correlated with values on the predictor scale.
  • the values on the points scale correlating with the patient's PSADT, PSABCR, GS, presence or absence of SVI, preRP PSA level, and/or the absence or extent of ECE 3 can be added together to yield a total points value, and the total points value can be correlated with the predictor scale to predict the quantitative probability of metastases progression in a prostate cancer patient with BCR after RP.
  • a method of using the nomogram is also provided.
  • the method includes providing a value for one, two or more patient factors, including PSADT, PSABR, GS, presence or absence of SVI, preRP PSA level, and/or absence or extent of ECE.
  • the values for the one or more factors are correlated with the probability of freedom from metastases progression in the patient.
  • the apparatus includes: a data input means, for input of information of one, two or more prostate cancer patient factors, factors including PSADT 5 PSABCR, GS, preRP PSA level, presence or absence of SVI, and/or absence or extent of ECE; a processor, executing a software for analysis of the information; wherein the software analyzes the information and provides the probability of freedom from metastases progression in the patient.
  • a method to predict the probability of freedom from metastases progression in a prostrate cancer patient with BCR after RP includes inputting information from a prostate cancer patient with BCR after RP to a data input means, where the information includes at least one, two, three, four, five or more patient factors, including at least one of PSADT, PSABCR, GS, preRP PSA level, the presence or absence of SVI, and/or the absence or extent of ECE; executing a software for analysis of the information; and analyzing the information so as to provide the probability of freedom from metastases progression in the patient.
  • the invention also provides an apparatus for predicting the probability of freedom from metastases progression in a prostate cancer patient with BCR after RP.
  • the apparatus includes a correlation of a set of factors for each of a plurality of persons with prostate cancer having BCR after RP, with the probability of freedom from metastases progression for each person of the plurality of persons.
  • the set of factors comprises one or more factors including PSADT, PSABCR, GS, the presence or absence of SVI, preRP PSA level, and/or the absence or extent of ECE.
  • the apparatus includes a means for comparing an identical set of factors determined from a patient having BCR after RP to the correlation to predict the quantitative probability of freedom from metastases progression in the patient.
  • Figures IA-B Disease states in prostate cancer.
  • the present invention provides methods, apparatus and nomograms to predict the probability of freedom from metastases progression in a prostate cancer patient with BCR after RP, to aid patients and physicians.
  • the invention provides methods, apparatus and nomograms to predict the probability of metastases progression in a prostate cancer patient with BCR after RP. Because the use of a single variable in predictive models, particularly for a disease with heterogenicity such as prostate cancer, is likely suboptimal, models that include multiple variables (e.g., nomograms) were developed. These models have been shown to be more accurate, measured by concordance index, than risk group assignment.
  • the pre- and post-operative variables were evaluated in a large cohort of patients with elevated serum PSA after RP for association with metastases progression. Those predictors were employed to construct a nomogram for predicting freedom from metastases progression or predicting metastases progression within 8 years of BCR.
  • One embodiment of the invention is directed to a method to predict the probability of freedom from metastases progression in a prostate cancer patient with BCR after RP, specifically in a patient not undergoing salvage RP, chemotherapy, or nonhormo ⁇ al therapy (NHT), while in other embodiments of the invention the patient may have undergone therapy for prostate cancer, e.g., radiation therapy.
  • the methods include detecting or determining a plurality of factors including at least two of PSADT, PSABCR, GS, the presence or absence of SVI, preRP PSA level, and/or the absence or extent of ECE, or any
  • the factors include at least PSADT and one or more of the following factors: PSABCR, SVI, and GS.
  • factors are employed which include GS, PSADT, and PSABCR.
  • the factors include ECE, SVI, GS, PSADT, and PSABCR.
  • the factors include ECE, PSADT, PSABCR, SVI and GS.
  • the correlating may be accomplished by computer. In one embodiment, the correlating includes accessing a memory storing the selected set of factors. In another embodiment, the correlating includes generating a functional representation and displaying the functional
  • the displaying includes transmitting the functional representation from a source.
  • the correlating is executed by a processor or a virtual computer program or interactive web site.
  • the method further includes transmitting the quantitative probability of freedom from metastases progression, or probability of metastases progression, in a prostate cancer patient with BCR after RP.
  • the method further includes inputting the identical set of factors for the patient within an input device.
  • the method further includes storing any of the set of factors to a memory or to a database.
  • the apparatus includes a data input means, for input of test information including one or more of the following factors: PSADT, PSABCR, GS, the presence or absence of SVI, preRP PSA level, and/or the absence or extent of ECE, a processor, executing a software for analysis of the amount, level or score of one or more of the factors and provides the probability of freedom from metastases progression or metastases progress in a prostate cancer patient with BCR after RP.
  • the nomogram may be generated with a Cox proportional hazards regression model (Cox, 1972). Alternatively, the nomogram may be generated with a neural network model (Rumelhart et al., 1986). In another embodiment, the nomogram is generated with a recursive partitioning model (Breiman et al., 1984). In yet another embodiment, the nomogram is generated with support vector machine technology (Cristianni et al., 2000). Other models known to those skilled in the art may alternatively be used. In one embodiment, the invention includes the use of software that implements Cox regression models or support vector machines to predict metastases progression, or freedom from metastases progression, in a patient with BCR after RP.
  • the nomogram may be a graphic representation of a probability of freedom from metastases progression or metastases progress.
  • the nomogram includes a set of indicia on a solid support, the indicia comprising one or more factor lines including a PSADT line, a SVI line, a preRP PSA level line, a GS line, a PSABCR level, and/or a ECE line, a points line, a total points line and a predictor line, wherein the PSADT line, SVI line, preRP PSA level line, GS line, PSABCR level line, and/or ECE line each have values on a scale which can be correlated with values on a scale on the points line.
  • the total points line has values on a scale which may be correlated with values on a scale on the predictor line, such that the value of each of the points correlating with the patient's PSADT, SVI, preRP PSA level, GS, PSABCR level, and/or ECE can be added together to yield a total points value.
  • the total points value can be correlated with the predictor line to predict the probability of freedom from metastases progression metastases progress.
  • the solid support may assume any appropriate form such as, for example, a laminated card. Any other suitable representation, picture, depiction or exemplification may be used.
  • the nomogram may assume any form, such as a computer program, e.g., in a hand-held device, world-wide- web page, e.g., written in FLASH, or a card, such as a laminated card. Any other suitable representation, picture, depiction or exemplification may be used.
  • the nomogram may comprise a graphic representation and/or may be stored in a database or memory, e.g., a random access memory, read-only memory, disk, virtual memory or processor.
  • the invention also provides an apparatus including a nomogram.
  • the apparatus including a nomogram may further comprise a storage mechanism, wherein the storage mechanism stores the nomogram; an input device that inputs the set of factors determined from a patient into the apparatus; and a display mechanism, wherein the display mechanism displays the quantitative probability of a positive bone scan in a prostate cancer patient with BCR after RP.
  • the storage mechanism may be random access memory, read-only memory, a disk, virtual memory, a database, and a processor.
  • the input device may be a keypad, a keyboard, stored data, a touch screen, a voice activated system, a
  • the display mechanism may be a computer monitor, a cathode ray tub (CRT), a digital screen, a light-emitting diode (LED), a liquid crystal display (LCD), an X-ray, a compressed digitized image, a video image, or a hand-held device.
  • CTR cathode ray tub
  • LED light-emitting diode
  • LCD liquid crystal display
  • the apparatus may further comprise a display that displays the quantitative probability of freedom from metastases or probability of metastases progression in a prostate cancer patient with BCR after RP, e.g., the display is separated from the processor such that the display receives the quantitative probability of freedom from metastases progression, or probability of metastases progression, in a prostate cancer patient with BCR after RP.
  • the apparatus may further comprise a database, wherein the database stores the correlation of factors and is accessible by the processor.
  • the apparatus may further comprise an input device that inputs the set of factors determined from the patient with BCR after RP into the apparatus.
  • the input device stores the set of factors in a storage mechanism that is accessible by the processor.
  • the apparatus may further comprise a transmission medium for transmitting the selected set of factors.
  • the transmission medium is coupled to the processor and the correlation of factors.
  • the apparatus may further comprise a transmission medium for transmitting the set of factors determined from the patient with BCR after RP, preferably the transmission medium is coupled to the processor and the correlation of factors.
  • the processor may be a multi-purpose or a dedicated processor.
  • the processor includes an object oriented program having libraries, said libraries storing said correlation of factors.
  • the nomograms of the present invention are also useful in clinical trials to identify patients appropriate for a trial, to quantify the expected benefit relative to baseline risk, to verify the effectiveness of randomization, to reduce the sample size requirements, and to facilitate comparisons across studies.
  • PSA progression biological recurrence, BCR
  • a single PSA > 0.4 ng/ml 19
  • salvage treatment XRT, HxRx
  • PSA doubling time PSADT was calculated by using all PSA values prior to reaching BCR; 570 (85%) had at least two PSA values for the PSADT calculations.
  • Pathology Gleason score, PSA doubling time, interval RP-BCR and PSA at time of BCR were used as continuous variables.
  • Metastases progression was identified in 141 patients, and of those 68 patients had non castrated metastases and 73 patients had castrated metastases. 491 patients were subjected to secondary treatment for PSA progression: 191 patients had external radiation and 300 patients received hormonal therapy for BCR only.
  • Table 2 shows the results for different predictors in a univariate analysis for metastases progression in BCR patients
  • Table 3 shows the results for different predictors in a multivariate analysis for metastases progression in BCR patients.
  • Table 4 shows the results for different predictors in a multivariate analysis that includes secondary treatments for metastases progression in BCR patients. Using the data, a nomogram was prepared ( Figure 2). Table 2
  • the present nomogram can be used to identify high risk patients for systemic progression, select candidates for salvage therapy following
  • biochemical failure and/or establish an accurate entry point for clinical trials, based on the probability of the individual patient having a systemic progression within 8 years from biochemical failure.

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biomedical Technology (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Physics & Mathematics (AREA)
  • Computer Hardware Design (AREA)
  • General Physics & Mathematics (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
  • Apparatus For Radiation Diagnosis (AREA)

Abstract

La présente invention concerne des procédés et un appareil pour la prédiction de la probabilité de l'absence de la progression de métastases chez de patients atteints du cancer de la prostate.
PCT/US2006/046643 2005-12-06 2006-12-06 Procede de prediction de progression systemique chez des patients atteints de cancer de la prostate Ceased WO2007067672A2 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US74301805P 2005-12-06 2005-12-06
US60/743,018 2005-12-06

Publications (2)

Publication Number Publication Date
WO2007067672A2 true WO2007067672A2 (fr) 2007-06-14
WO2007067672A3 WO2007067672A3 (fr) 2008-05-08

Family

ID=38016820

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2006/046643 Ceased WO2007067672A2 (fr) 2005-12-06 2006-12-06 Procede de prediction de progression systemique chez des patients atteints de cancer de la prostate

Country Status (1)

Country Link
WO (1) WO2007067672A2 (fr)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9605319B2 (en) 2010-08-30 2017-03-28 Myriad Genetics, Inc. Gene signatures for cancer diagnosis and prognosis
US9976188B2 (en) 2009-01-07 2018-05-22 Myriad Genetics, Inc. Cancer biomarkers
US10876164B2 (en) 2012-11-16 2020-12-29 Myriad Genetics, Inc. Gene signatures for cancer prognosis
US10954568B2 (en) 2010-07-07 2021-03-23 Myriad Genetics, Inc. Gene signatures for cancer prognosis
US11174517B2 (en) 2014-05-13 2021-11-16 Myriad Genetics, Inc. Gene signatures for cancer prognosis

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5993388A (en) * 1997-07-01 1999-11-30 Kattan; Michael W. Nomograms to aid in the treatment of prostatic cancer
US20030235816A1 (en) * 2002-03-14 2003-12-25 Baylor College Of Medicine (By Slawin And Shariat) Method to determine outcome for patients with prostatic disease
CA2547616A1 (fr) * 2003-11-26 2005-06-16 Memorial Sloan-Kettering Cancer Center Procede de prevision d'une biopsie de la prostate a repetition positive
AU2005220980A1 (en) * 2004-03-11 2005-09-22 Baylor College Of Medicine Method to predict risk of BPH progression
US20050282199A1 (en) * 2004-05-11 2005-12-22 Slawin Kevin M Method to predict prostate cancer

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9976188B2 (en) 2009-01-07 2018-05-22 Myriad Genetics, Inc. Cancer biomarkers
US10519513B2 (en) 2009-01-07 2019-12-31 Myriad Genetics, Inc. Cancer Biomarkers
US10954568B2 (en) 2010-07-07 2021-03-23 Myriad Genetics, Inc. Gene signatures for cancer prognosis
US9605319B2 (en) 2010-08-30 2017-03-28 Myriad Genetics, Inc. Gene signatures for cancer diagnosis and prognosis
US10876164B2 (en) 2012-11-16 2020-12-29 Myriad Genetics, Inc. Gene signatures for cancer prognosis
US11174517B2 (en) 2014-05-13 2021-11-16 Myriad Genetics, Inc. Gene signatures for cancer prognosis

Also Published As

Publication number Publication date
WO2007067672A3 (fr) 2008-05-08

Similar Documents

Publication Publication Date Title
Catalona et al. Use of the percentage of free prostate-specific antigen to enhance differentiation of prostate cancer from benign prostatic disease: a prospective multicenter clinical trial
Kattan et al. Postoperative nomogram for disease recurrence after radical prostatectomy for prostate cancer
US6409664B1 (en) Nomograms to aid in the treatment of prostatic cancer
Dalal et al. Subtype specific prognostic nomogram for patients with primary liposarcoma of the retroperitoneum, extremity, or trunk
Spratt et al. Individual patient-level meta-analysis of the performance of the decipher genomic classifier in high-risk men after prostatectomy to predict development of metastatic disease
Stephenson et al. Do margins matter? The influence of positive surgical margins on prostate cancer–specific mortality
Moul 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
Domchek et al. Application of breast cancer risk prediction models in clinical practice
Pound et al. Natural history of progression after PSA elevation following radical prostatectomy
Alkhateeb et al. Impact of positive surgical margins after radical prostatectomy differs by disease risk group
US5993388A (en) Nomograms to aid in the treatment of prostatic cancer
Wu et al. Development and validation of a 32-gene prognostic index for prostate cancer progression
Quinn et al. Prognostic significance of pathologic features in localized prostate cancer treated with radical prostatectomy: implications for staging systems and predictive models
Rodriguez-Urrego et al. Interobserver and intraobserver reproducibility in digital and routine microscopic assessment of prostate needle biopsies
Freedland et al. PSA in the new millennium: a powerful predictor of prostate cancer prognosis and radical prostatectomy outcomes—results from the SEARCH database
Pathi et al. Utility of clinical parameters, cystourethroscopy, and magnetic resonance imaging in the preoperative diagnosis of urethral diverticula
Teeter et al. Do nomograms designed to predict biochemical recurrence (BCR) do a better job of predicting more clinically relevant prostate cancer outcomes than BCR? A report from the SEARCH database group
US20050282199A1 (en) Method to predict prostate cancer
Mitsuzuka et al. Is pelvic lymph node dissection required at radical prostatectomy for low‐risk prostate cancer?
Ledezma et al. Robotic-assisted pelvic lymph node dissection for prostate cancer: frequency of nodal metastases and oncological outcomes
WO2007067672A2 (fr) Procede de prediction de progression systemique chez des patients atteints de cancer de la prostate
Gomez Cifuentes et al. New model to predict recurrence after endoscopic mucosal resection of non-pedunculated colonic polyps≥ 20 mm
Bhojani et al. Partin tables cannot accurately predict the pathological stage at radical prostatectomy
Perry et al. Point shear wave elastography in assessment of hepatic fibrosis: diagnostic accuracy in subjects with native and transplanted livers referred for percutaneous biopsy
US20050019798A1 (en) Methods to predict death from breast cancer

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application
NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 06844933

Country of ref document: EP

Kind code of ref document: A2