Survival and Cardiovascular Events with TRT

[Michael Scally MD]

Wallis CJD, Lo K, Lee Y, et al. Survival and cardiovascular events in men treated with testosterone replacement therapy: an intention-to-treat observational cohort study. The Lancet Diabetes & Endocrinology. http://www.thelancet.com/journals/landia/article/PIIS2213-8587(16)00112-1/abstract

Background - Conflicting evidence exists for the association between testosterone replacement therapy and mortality and cardiovascular events. The US Food and Drug Administration recently cautioned that testosterone replacement therapy might increase risk of heart attack and stroke, based on evidence from studies with short treatment duration and follow-up. No previous study has assessed the effect of duration of testosterone treatment on these outcomes. We aimed to assess the association between long-term use of testosterone replacement therapy and mortality, cardiovascular events, and prostate cancer diagnoses, using a time-varying exposure analysis.

Methods - We did a population-based matched cohort study of men aged 66 years or older newly treated with testosterone replacement therapy and controls matched for age, region of residence, comorbidity, diabetes status, and index year from 2007–12 in Ontario, Canada, using data from the Ontario Drug Benefit database, the Canadian Institute for Health Information (CIHI) Discharge Abstract Database, the CIHI National Ambulatory Care Reporting System, the Ontario Health Insurance Plan database, the Ontario Myocardial Infarction Database, the Ontario Diabetes Database, the Ontario Cancer Registry, and the Registered Persons database. We assessed the association between cumulative testosterone replacement therapy exposure and mortality, cardiovascular events, and prostate cancer using marginal models with a time-varying testosterone exposure.

Findings - We included 10 311 men treated with testosterone replacement therapy and 28 029 controls between Jan 1, 2007, and June 30, 2012.

Over a median follow-up of 5·3 years (IQR 3·6–7·5) in the testosterone replacement therapy group and 5·1 years (3·4–7·4) in the control group, patients treated with testosterone replacement therapy had lower mortality than did controls (hazard ratio

---

0·88, 95% CI 0·84–0·93).

Patients in the lowest tertile of testosterone exposure had increased risk of mortality (HR 1·11, 95% CI 1·03–1·20) and cardiovascular events (HR 1·26, 95% CI 1·09–1·46) compared with controls.

By contrast, those in the highest tertile of testosterone exposure had decreased risk of mortality (HR 0·67, 95% CI 0·62–0·73) and cardiovascular events (HR 0·84, 95% CI 0·72–0·98), with a significant trend across tertiles (p<0·0001).

Risk of prostate cancer diagnosis was decreased for those with the highest tertile of exposure (HR 0·60, 95% CI 0·45–0·80) compared with controls, but not for those with the shortest exposure.

Interpretation - Long-term exposure to testosterone replacement therapy was associated with reduced risks of mortality, cardiovascular events, and prostate cancer. However, testosterone replacement therapy increased the risk of mortality and cardiovascular events with short durations of therapy. In view of the limitations of observational data and the potential for selection bias, these results warrant confirmation in a randomised trial.

 

[Dr JIM]

It's really difficult to estimate the impact of TRT on CV mortality using such a brief observation interval, as the authors already mentioned.

 

[Michael Scally MD]

Wallis CJD, Saskin R, Narod SA, et al. Estimating the effect of immortal-time bias in urologic research: a case example of testosterone-replacement therapy. BJU Int. http://onlinelibrary.wiley.com/doi/10.1111/bju.13918/abstract

OBJECTIVE: To quantify the effect of immortal-time bias in an observational study examining the effect of cumulative testosterone exposure on mortality.

SUBJECTS AND METHODS: We used a population-based matched cohort study of men aged 66 and older newly treated with testosterone replacement therapy and matched-controls from 2007-2012 in Ontario, Canada to quantify the effects of immortal-time bias. We used generalized estimating equations to determine the association between cumulative testosterone replacement therapy exposure and mortality. Results produced by models using time-fixed and time-varying exposures were compared. Further, we undertook a systematic review of PubMed to identify studies addressing immortal-time bias or time-varying exposures in the urologic literature and qualitative summated these.

RESULTS: Among 10,311 TRT-exposed men and 28,029 controls, the use of a time-varying exposure resulted in the attenuation of treatment effects compared with an analysis which did not account for immortal-time bias.

While both analyses showed a decreased risk of death for patients in the highest tertile of TRT exposure, the effect was overestimated when using a time-fixed analysis (aHR 0.56, 95% CI 0.52-0.61) when compared to a time-varying analysis (aHR 0.67, 95% CI 0.62-0.73).

Of the 1241 studies employing survival analysis identified in the literature, nine manuscripts met criteria for inclusion. Of these, 5 employed time-varying analytic methodology. Each of these was a large, population-based retrospective cohort study assessing potential harms of pharmacologic agents.

CONCLUSIONS: Where exposures vary over time, a time-varying exposure is necessary to draw meaningful conclusions. Failure to employ a time-varying analysis will result in overestimation of a beneficial effect. However, time-varying exposures are uncommonly utilized among manuscripts published in prominent urologic journals.

 

[Michael Scally MD]

Wallis CJD, Saskin R, Narod SA, et al. Estimating the effect of immortal-time bias in urologic research: a case example of testosterone-replacement therapy. BJU Int. http://onlinelibrary.wiley.com/doi/10.1111/bju.13918/abstract

OBJECTIVE: To quantify the effect of immortal-time bias in an observational study examining the effect of cumulative testosterone exposure on mortality.

SUBJECTS AND METHODS: We used a population-based matched cohort study of men aged 66 and older newly treated with testosterone replacement therapy and matched-controls from 2007-2012 in Ontario, Canada to quantify the effects of immortal-time bias. We used generalized estimating equations to determine the association between cumulative testosterone replacement therapy exposure and mortality. Results produced by models using time-fixed and time-varying exposures were compared. Further, we undertook a systematic review of PubMed to identify studies addressing immortal-time bias or time-varying exposures in the urologic literature and qualitative summated these.

RESULTS: Among 10,311 TRT-exposed men and 28,029 controls, the use of a time-varying exposure resulted in the attenuation of treatment effects compared with an analysis which did not account for immortal-time bias.

While both analyses showed a decreased risk of death for patients in the highest tertile of TRT exposure, the effect was overestimated when using a time-fixed analysis (aHR 0.56, 95% CI 0.52-0.61) when compared to a time-varying analysis (aHR 0.67, 95% CI 0.62-0.73).

Of the 1241 studies employing survival analysis identified in the literature, nine manuscripts met criteria for inclusion. Of these, 5 employed time-varying analytic methodology. Each of these was a large, population-based retrospective cohort study assessing potential harms of pharmacologic agents.

CONCLUSIONS: Where exposures vary over time, a time-varying exposure is necessary to draw meaningful conclusions. Failure to employ a time-varying analysis will result in overestimation of a beneficial effect. However, time-varying exposures are uncommonly utilized among manuscripts published in prominent urologic journals.

Fletcher SA, Gild P, Trinh Q-D. Immortal-time bias: a crucial yet overlooked confounder in urological research. BJU International 2017;120(4):455-. http://onlinelibrary.wiley.com/doi/10.1111/bju.13966/full

The measurement of treatment effect through observational studies has become commonplace in the medical literature. These cohort studies provide valuable data on outcomes that can be difficult to assess in randomized controlled trials, such as long-term mortality.

Accurate interpretation of observational data, however, requires accounting for potential confounders of study design, including the immortal-time bias.

In this issue of BJUI, Wallis et al. show how accounting for this bias can influence the measured effect of cumulative testosterone exposure on mortality.

The implications of their findings extend to several other studies, whose designs may also be subject to immortal-time bias.

…

 

[grey]

including the immortal-time bias.

I had to look that up... I barely grasp the implications of it here, other than to highlight the facts that I need to study more statistical analysis techniques...

 

[Dr JIM]

I had to look that up... I barely grasp the implications of it here, other than to highlight the facts that I need to study more statistical analysis techniques...

Part of the problem in assessing “TRT” data is sorting out The Who were the patients (young vs old) What Dose, and for How Long. (Of course another limitation is TRT has been a “mainstream” form of therapy for roughly ten years)

Next up let’s investigste How the above info reported and collated.

Then let’s run some numbers using a variety of statistical “methodioligies” and proceed from there.

Althought such info may be an interesting read for the select few who have time to wade thru all the statistics , it’s difficult to apply such info from a clinical perspective IMO.

Jim

 

[Old]

Forms of testosterone should also be tracked and interpreted.

For example, topical T gel/patches have relative short half life and should reach steady-state in about a week. It also produces more DHT than injectable forms, even when applied correctly. In USA, injectable is often 200mg every 2 weeks. This creates a spike of supraphysioligical levels that slowly decay to near hypogonadism before the next injection (since half life of TC is < 1 week).

Not accurately accounting for these details clouds info. Does the extra DHT help or hurt mortality? Does the extreme swing in blood levels for 200mg/2 weeks harm mortality figures?... it certainly does not even try to mimic a circadian rhythm.

Then there has been the failure to track ACTUAL free T. The quartile/mortality data for free T is greater than for all T. And when are they tracking E2 - a very significant hormone?


A huge problem is underpowered and underfunded studies. But just to try to track a couple hundred thousand people for 10 or 20 or 30 years for mortality data could easily cost a billion dollars.

Studies that sweep pubmed for data and present patterns end up skipping relevant info such as dose, how long, and other info posted above.

We just have to work with what is being done. Its better then just looking at rat studies.


The short-term/long-term difference in mortality is important. The long-term TRT mortality by quartile matches what has already been observed in natural T levels by quartile - - - those who are in the 4th quartile live longer than those in 1st quartile. No favors have been done by the recent downward redefinition of 'healthy' range. This is political, not science.

 

[Dr JIM]

Forms of testosterone should also be tracked and interpreted.

For example, topical T gel/patches have relative short half life and should reach steady-state in about a week. It also produces more DHT than injectable forms, even when applied correctly. In USA, injectable is often 200mg every 2 weeks. This creates a spike of supraphysioligical levels that slowly decay to near hypogonadism before the next injection (since half life of TC is < 1 week).

Not accurately accounting for these details clouds info. Does the extra DHT help or hurt mortality? Does the extreme swing in blood levels for 200mg/2 weeks harm mortality figures?... it certainly does not even try to mimic a circadian rhythm.

Then there has been the failure to track ACTUAL free T. The quartile/mortality data for free T is greater than for all T. And when are they tracking E2 - a very significant hormone?


A huge problem is underpowered and underfunded studies. But just to try to track a couple hundred thousand people for 10 or 20 or 30 years for mortality data could easily cost a billion dollars.

Studies that sweep pubmed for data and present patterns end up skipping relevant info such as dose, how long, and other info posted above.

We just have to work with what is being done. Its better then just looking at rat studies.


The short-term/long-term difference in mortality is important. The long-term TRT mortality by quartile matches what has already been observed in natural T levels by quartile - - - those who are in the 4th quartile live longer than those in 1st quartile. No favors have been done by the recent downward redefinition of 'healthy' range. This is political, not science.

The fact this metanalysis screened 1241 studies yet only found FIVE qualifiers is telling.

A large portion of this “research” is much to do about nothing primarily bc the adverse effects of LEGITIMATE TRT are minimal.

To that end I doubt any study now or in the near future will determine the “TRT RISK” in real terms.