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      PSA and PSA Kinetics as Predictors for 18F-Fluciclovine PET/CT Positivity in Biochemically Recurrent Prostate Cancer

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          Abstract

          Introduction: 18F-Fluciclovine PET/CT is one of the imaging techniques currently employed to restage prostate cancer (PCa). Due to the conflicting results reported in the literature, it is not yet known at what PSA threshold 18F-fluciclovine PET/CT could reliably demonstrate the presence of recurring disease. We explored the association between 18F-fluciclovine PET/CT positivity and prescan PSA, PSA doubling time, and PSA velocity in patients with biochemical recurrence (BCR) of PCa after curative-intent treatment. Methods: Data from 59 patients who underwent 18F-fluciclovine PET/CT for BCR after radical prostatectomy or radiotherapy were retrieved from a single institution database. Patients already undergone salvage treatments at the time of PET/CT, with newly diagnosed PCa or with initial diagnosis of metastatic PCa were excluded. A 2-sided independent samples Bayesian t test and Bayesian Mann-Whitney U test were used to assess the association between PET/CT and prescan PSA, PSA doubling time, and PSA velocity. Results: Evidence for no difference between PET/CT-positive and -negative patients for log-transformed PSA was found (BF01 3.61, % error: 0.01). Robustness check and sequential analysis showed stability across a wide range of prior distribution specifications. The hypothesis of no difference in terms of PSA-dt and for PSA-vel between groups was found to be more likely compared to the alternative hypothesis (BF01 of 3.44 and 3.48, respectively). Conclusion: PSA and PSA kinetics are unlikely to be associated with 18F-fluciclovine PET/CT positivity in patients with BCR, and none of these serum biomarkers might be used as single predictors of PET/CT detection. Larger studies might be needed to evaluate the role of different predictors.

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          Bayesian t tests for accepting and rejecting the null hypothesis.

          Progress in science often comes from discovering invariances in relationships among variables; these invariances often correspond to null hypotheses. As is commonly known, it is not possible to state evidence for the null hypothesis in conventional significance testing. Here we highlight a Bayes factor alternative to the conventional t test that will allow researchers to express preference for either the null hypothesis or the alternative. The Bayes factor has a natural and straightforward interpretation, is based on reasonable assumptions, and has better properties than other methods of inference that have been advocated in the psychological literature. To facilitate use of the Bayes factor, we provide an easy-to-use, Web-based program that performs the necessary calculations.
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            Is Open Access

            Using Bayes to get the most out of non-significant results

            No scientific conclusion follows automatically from a statistically non-significant result, yet people routinely use non-significant results to guide conclusions about the status of theories (or the effectiveness of practices). To know whether a non-significant result counts against a theory, or if it just indicates data insensitivity, researchers must use one of: power, intervals (such as confidence or credibility intervals), or else an indicator of the relative evidence for one theory over another, such as a Bayes factor. I argue Bayes factors allow theory to be linked to data in a way that overcomes the weaknesses of the other approaches. Specifically, Bayes factors use the data themselves to determine their sensitivity in distinguishing theories (unlike power), and they make use of those aspects of a theory’s predictions that are often easiest to specify (unlike power and intervals, which require specifying the minimal interesting value in order to address theory). Bayes factors provide a coherent approach to determining whether non-significant results support a null hypothesis over a theory, or whether the data are just insensitive. They allow accepting and rejecting the null hypothesis to be put on an equal footing. Concrete examples are provided to indicate the range of application of a simple online Bayes calculator, which reveal both the strengths and weaknesses of Bayes factors.
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              Natural history of progression after PSA elevation following radical prostatectomy.

              In men who develop an elevated serum prostate-specific antigen level (PSA) after having undergone a radical prostatectomy, the natural history of progression to distant metastases and death due to prostate cancer is unknown. To characterize the time course of disease progression in men with biochemical recurrence after radical prostatectomy. A retrospective review of a large surgical series with median (SD) follow-up of 5.3 (3.7) years (range, 0.5-15 years) between April 1982 and April 1997. An urban academic tertiary referral institution. A total of 1997 men undergoing radical prostatectomy, by a single surgeon, for clinically localized prostate cancer. None received neoadjuvant therapy, and none had received adjuvant hormonal therapy prior to documented distant metastases. After surgery, men were followed up with PSA assays and digital rectal examinations every 3 months for the first year, semiannually for the second year, and annually thereafter. A detectable serum PSA level of at least 0.2 ng/mL was evidence of biochemical recurrence. Distant metastases were diagnosed by radionuclide bone scan, chest radiograph, or other body imaging, which was performed at the time of biochemical recurrence and annually thereafter. The actuarial metastasis-free survival for all 1997 men was 82% (95% confidence interval, 76%-88%) at 15 years after surgery. Of the 1997 men, 315 (15%) developed biochemical PSA level elevation. Eleven of these underwent early hormone therapy after the recurrence and are not included in the study. Of the remaining 304 men, 103 (34%) developed metastatic disease within the study period. The median actuarial time to metastases was 8 years from the time of PSA level elevation. In survival analysis, time to biochemical progression (P<.001), Gleason score (P<.001), and PSA doubling time (P<.001) were predictive of the probability and time to the development of metastatic disease. An algorithm combining these parameters was constructed to stratify men into risk groups. Once men developed metastatic disease, the median actuarial time to death was 5 years. The time interval from surgery to the appearance of metastatic disease was predictive of time until death (P<.02). Several clinical parameters help predict the outcomes of men with PSA elevation after radical prostatectomy. These data may be useful in the design of clinical trials, the identification of men for enrollment into experimental protocols, and counseling men regarding the timing of administration of adjuvant therapies.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Urologia Internationalis
                Urol Int
                S. Karger AG
                0042-1138
                1423-0399
                December 21 2021
                : 1-8
                Article
                10.1159/000520684
                08b936b9-1e47-4c63-86ed-5b6c5dcc74d3
                © 2021

                https://www.karger.com/Services/SiteLicenses

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