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  string(123) "External Validation  of a Prognostic Model of Overall Survival  In Men with Metastatic Castration-Resistant Prostate Cancer"
  ["project_narrative_summary"]=>
  string(604) "Background: We have previously developed and externally validated a prognostic model of overall survival (OS) in men with mCRPC treated with docetaxel (D), which included eight predictors: opioid analgesic use, ECOG performance status, albumin, disease site, LDH, hemoglobin, PSA, and alkaline phosphatase. We have used this model to develop prognostic risk groups. We seek to externally validate this model in a broader group of men with mCRPC and in specific subgroups (White, Black, Asian patients, different age groups) and to validate the two and three prognostic risk groups in this large dataset ."
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      string(4) "Yang"
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      string(3) "Luo"
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      string(6) "Siyuan"
      ["p_pers_l_name"]=>
      string(3) "Guo"
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      string(5) "Akash"
      ["p_pers_l_name"]=>
      string(3) "Roy"
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      string(15) "Duke University"
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    ["label"]=>
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  ["project_funding_source"]=>
  string(11) "NIH and DOD"
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      string(278) "NCT02257736 - A Phase 3 Randomized, Placebo-controlled Double-blind Study of JNJ-56021927 in Combination With Abiraterone Acetate and Prednisone Versus Abiraterone Acetate and Prednisone in Subjects With Chemotherapy-naive Metastatic Castration-resistant Prostate Cancer (mCRPC)"
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  ["property_scientific_abstract"]=>
  string(2519) "We have previously developed and externally validated a prognostic model of overall survival (OS) in men with mCRPC treated with docetaxel (D), which included eight predictors [1]. This model was developed in patients treated with D and we would like generalize this model  to contemporary patients in the era of potent AR inhibition with agents such as enzalutamide (ENZA) , abiraterone acetate (AA) and apalutamide (APA).

Objective; We seek to externally validate this prognostic model in a broader group of men with mCRPC and in specific subgroups (racial and ethnic group and  different age groups) and to validate the two and three prognostic risk groups in this large dataset.

Study Design:  This is a pooled analyses that will utilizine data from over 8000 mCRPC men randomized on 7 phase III trials to validate the prognostic model of OS: docetaxel (D) +/- zibotentan (ENTHUSE), D +/- lenalidomide (MAINSAIL), D +/- dasatinib (READY), D+/- custirsen (SYNERGY), tasquinimod trial (T/placebo), ENZA+/-AAP (A031201) and  ACIS (AAP  +/- APA) .

Participants: Men with mCRPC.

Main Outcome Measure(s);  is OS and will be defined as the time from date of random assignment to date of death of any cause or last follow-up.

Statistical Analysis: We will evaluate the predictive ability of the prognostic model based on discrimination and calibration. We will first apply the estimated parameters from the prognostic model to each of the seven validation datasets and compute a risk score for every patient. The predictive performance of the model will be evaluated by computing the time-dependent area under the receiver operating characteristic curve (tAUC) for each of the validation sets. In addition, we will evaluate the performance of the prognostic model in subgroup of patients, in patients treated on the standard arm alone, in Asian, Black, and white patients and by age groups. Furthermore, we will calculate the 95% CI for each tAUC using the bootstrap approach. The prognostic model will be assessed for its calibration. In addition, we will validate the prognostic risk groups by comparing the survival distributions between the high-risk and low-risk groups, or the high-risk, intermediate-risk, or the low-risk groups. The Kaplan-Meier approach will be used to estimate the OS distribution in every dataset and the log-rank statistic will be used separately in the seven datasets to test if the survival distributions differed by the two or three prognostic risk groups."
  ["project_brief_bg"]=>
  string(1769) "Prostate cancer is heterogeneous in all stages of disease both in terms of clinical behavior and morphology, with development and progression dependent upon androgens and androgen receptor (AR) activity. The tumor is initially androgen dependent but eventually it progresses to become androgen independent . Current front-line therapies for men with metastatic, castration-resistant prostate cancer (mCRPC) are androgen receptor targeted therapy, chemotherapy, and bone targeting agents [2-9].

The difficulty in treating men with mCRPC lies not only in heterogeneity of the disease (tumor specific factors), but also in the spectrum of patients who have the disease (host-specific factors). Thus, the variability in the expected outcome may be due to prognostic factors rather than in differences in treatments.

	We have previously developed a prognostic model that predicts overall survival probability in men with metastatic castration-resistant prostate cancer (mCRPC) who were treated with first line docetaxel chemotherapy. The model was externally validated using the Enthuse-33 trial in patients treated with docetaxel and prednisone. The model has been used as a stratification factor in an ongoing phase II (NCT02218606) and a completed phase III mCRPC trials (NCT01949337).   Currently, the prognostic risk score is used in selecting patients and to balance the prognostic factors between the treatment arms at randomization.  This prognostic model was developed in patients with docetaxel and we would like generalize this model  to contemporary patients in the era of potent AR inhibition with agents such as enzalutamide , abiraterone acetate and apalutamide. In addition, the performance of this model was not evaluated in diverse population"
  ["project_specific_aims"]=>
  string(969) "We seek to validate the risk score generated by the prognostic model by using external datasets in patients treated with docetaxel and in patients who were treated on tasquinimod, and in patients treated with AR inhibition (abiraterone acetate or enzalutamide, apalutamide)  and to validate the two and three prognostic risk groups.  Thus, the primary objectives of this analysis is to externally validate the prognostic model of OS in a broader group of men with mCRPC. In addition, we plan to explore the predictive accuracy of the model in specific racial and age subgroups and treatment received and to validate the two and three prognostic risk group that is created by the model.

We are investigating the impact of liver metastases on clinical outcomes (OS, rPFS, ORR and PSA decline). We are also aiming to characterize exceptional responders and extreme resistance.

For last two of these aims, we plan to combine the data with other trial datasets"
  ["project_study_design"]=>
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    ["value"]=>
    string(7) "meta_an"
    ["label"]=>
    string(52) "Meta-analysis (analysis of multiple trials together)"
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  ["project_purposes"]=>
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      ["label"]=>
      string(114) "New research question to examine treatment effectiveness on secondary endpoints and/or within subgroup populations"
    }
  }
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    ["label"]=>
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  ["project_research_methods"]=>
  string(767) "Data from over 8000 mCRPC men randomized on 7 phase III trials will be utilized to validate the prognostic model of OS: D +/- zibotentan (ENTHUSE), D +/- lenalidomide (MAINSAIL), D +/- dasatinib (READY), D+/- custirsen (SYNERGY), tasquinimod/placebo phase 3 trial, enzalutamide+/- abiraterone trial from the Alliance trial (A031201trial) and the ACIS trial  (abiraterone acetate  +/- apalutamide) . We have access to the data from the 6 other trials and will be uploaded to the YODA platform to combine it with the data from the ACIS trial. Data are available through DUA with the sponsors on these trials:

ENTHUSE-33 (NCT00617669), READY (NCT00744497), MAINSAIL (NCT00988208), SYNERGY (NCT01188187), TASQUINIMOD (NCT01234311) and A031201

(NCT01949337)."
  ["project_main_outcome_measure"]=>
  string(381) "The primary endpoint is overall survival (OS) and will be defined as the time from date of random assignment to date of death of any cause or last follow-up.

1.	Date of Randomization (MM/DD/YYYY)

2.	Survival Status (Alive, dead)

3.	Date of Last Observation or Follow-up (MM/DD/YYYY)

4.	Date of Death (MM/DD/YYYY) or time to death since random assignment"
  ["project_main_predictor_indep"]=>
  string(380) "The main predictors are:

1. ECOG Performance Status: 0, 1, 2, 3+

2.	Opioid analgesic use 1) Yes, 2) No

3.	Measurable Disease: 1) Yes, 2) No

4.	Site of metastases: 1) Lymph nodes, 2) Bone, 3) Lung, 4) Liver, 5) other visceral metastases

5.  LDH (and ULN for LDH)

6. Hemoglobin

7. PSA

8. Alkaline phosphatase

9. Albumin"
  ["project_other_variables_interest"]=>
  string(400) "In addition, age, race and ethnicity will be needed to describe the population and to assess the performance of the model in these subgroups.

1. Age (years)

2.Race

White

Black or African American

Asian

American Indian or Alaska Native

Missing/Not reported

3. Ethnicity

Hispanic or Latino

Not Hispanic or Latino

Not Reported"
  ["project_stat_analysis_plan"]=>
  string(1460) "We will evaluate the predictive ability of the prognostic model based on discrimination and calibration. We will first apply the estimated parameters from the prognostic model to each of the seven validation datasets and compute a risk score for every patient. The predictive performance of the model will be evaluated by computing the time-dependent area under the receiver operating characteristic curve (tAUC) for each of the validation sets [10]. In addition, we will evaluate the performance of the prognostic model in subgroup of patients, in patients treated on the standard arm alone, in Asian, Black, and white patients and by age groups. Furthermore, we will calculate the 95% CI for each tAUC using the bootstrap approach.

	The prognostic model will be assessed for its calibration graphically by plotting the predicted probability of death evaluated at 18-, 22- 24-, and 30- months versus the observed probability at the respective time-points. In addition, we will validate the prognostic risk groups by comparing the survival distributions between the high-risk and low-risk groups (for two-risk group), or the high-risk, intermediate-risk, or the low-risk groups (in case of the three-risk group). The Kaplan-Meier approach will be used to estimate the OS distribution in every dataset and the log-rank statistic will be used separately in the seven datasets to test if the survival distributions differed by the two or three risk groups."
  ["project_timeline"]=>
  string(358) "We plan to submit an abstract for ESMO in late April/May 2022. We have access to all the datasets except the ACIS trial. It is expected that it will take 6 months to complete the analysis. It is anticipated that a manuscript will be submitted by December 2022.

We are still assembling additional data and plan to complete the analysis by December 2025"
  ["project_dissemination_plan"]=>
  string(781) "The results of these analyses will be submitted as abstracts and will be presented at International meetings such as ESMO and the Prostate Cancer Foundation Scientific Retreat. The first abstract is planned for  ESMO in  April/May 2022. Manuscripts will be written and will be submitted for Publication in peer review journals, such as Journal of Clinical Oncology, and Journal of the National Cancer Institute.  Abstracts and manuscripts will be sent to the sponsor for review.

An  abstract is planned for  ESMO in  April/May 2024. Manuscripts will be written and will be submitted for Publication in peer review journals, such as Journal of Clinical Oncology, and Journal of the National Cancer Institute.  Abstracts and manuscripts will be sent to the sponsor for review."
  ["project_bibliography"]=>
  string(1949) "
1. Halabi S, Lin CY, Kelly WK, at al: Updated prognostic model for predicting overall survival in first-line chemotherapy for patients with metastatic castration-resistant prostate cancer. J Clin Oncol. 32:671-677, 2014

2. Kantoff PW, Higano CS, Shore ND, et al: Sipuleucel-T immunotherapy for castration resistant prostate cancer. N Engl J Med 363:411-422, 2010

3. de Bono JS, Logothetis CJ, Molina A, et al: Abiraterone and increased survival in metastatic prostate cancer. N Engl J Med 364:1995-2005, 2011

4. Fizazi K, Carducci M, Smith M, et al: Denosumab versus zoledronic acid for treatment of bone metastases in men with castration-resistant prostate cancer: a randomised, double blind study. Lancet 377:813-822, 2011

5. Ryan CJ, Smith MR, De Bono JS, et al: Abiraterone in metastatic prostate cancer without previous chemotherapy. N Engl J Med 368:138-48, 2013

6. Scher HI, Fizazi K, Saad F, et al: Increased survival with enzalutamide in prostate cancer after chemotherapy. N Engl J Med 367:1187-97, 2012

7. de Bono JS, Oudard S, Ozguroglu M, et al: Prednisone plus cabazitaxel or mitoxantrone for metastatic castration-resistant prostate cancer progressing after docetaxel treatment: a randomised open-label trial. Lancet 376:1147-1154, 2010

8. Parker C, Nilsson S, Heinrich D, et al: Alpha emitter radium-223 and survival in metastatic prostate cancer. N Engl J Med 369:213-23, 2013

9. Saad F, Efstathiou E, Attard G, et al: Apalutamide plus abiraterone acetate and prednisone versus placebo plus abiraterone and prednisone in metastatic, castration-resistant prostate cancer (ACIS): a randomised, placebo-controlled, double-blind, multinational, phase 3 study. Lancet Oncol. 22:1541-1559, 2021.

10. Uno H, Cai T, Tian L, et al: Evaluating prediction rules for t-year survivors with censored regression models. Journal of the American Statistical Association 102:527-537, 2007
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  ["project_review_link"]=>
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    ["id"]=>
    int(10650)
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data partner
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pi country
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}


pi affil
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}


products
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}


num of trials
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}


res
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}