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Improving the clinical management of HIV infection
Improving the clinical management of HIV infection

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New predictive computer models designed to optimize HIV therapy in countries with limited healthcare resources are published online this week in the Journal of Antimicrobial Chemotherapy (JAC). The models, which were developed with data from tens of thousands of patients around the world, accurately predict how an individual on failing therapy will respond to any new combination of HIV drugs.

The publication describes two new sets of models: one that does not require the genetic code of the virus, for use settings where HIV genotyping tests are unavailable, and another that includes this information for use in well-resourced settings. Both sets of models were developed with relaxed requirements for input data, again to suit low to middle income countries.

Both sets of models predicted the responses to the new regimen introduced in the clinic with approximately 80% accuracy. They were significantly more accurate than using genotyping, with state of the art interpretation, to predict responses. Both sets of models were able to identify combinations of locally available drugs that were predicted to produce a response in 90% or more of the cases that failed the new combination introduced in the clinic.

“These models represent a significant step forward towards the individualisation of HIV therapy in countries where genotyping is unavailable, treatment options are limited, and the selection of the best combination is particularly critical,” commented Dr Brendan Larder, Scientific Chair of the RDI and an author on the paper.

https://www.hivrdi.org/new-predictive-models-for-individualising-hiv-therapy-in-countries-with-limited-resources-press-release-72.htm
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New computer models launched today on World AIDS Day predict how patients whose HIV therapy is failing will respond to any new combination of drugs, with around 80% accuracy. The models, which were developed using data from tens of thousands of patients around the world, require far less recent patient data than previous models, making them particularly useful for settings with infrequent clinic visits such as low-income or rural settings.

“The development and performance of these models that have much more practical data requirements is extremely encouraging”, commented Professor Robin Wood, Director of the Desmond Tutu HIV Centre, University of Cape Town, South Africa and one of the key contributors of data to the study. “This will significantly increase the utility of the system in Southern Africa and other low-resource settings, which is just what we need to help optimise treatment and combat increasing levels of drug resistance.”

The new models are now available to be used by healthcare professionals as part of the RDI’s HIV Treatment Response Prediction System (HIV-TRePS), which is freely available online at https://www.hivrdi.org/treps

#Worldaidsday #WAD2017 #HIV
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The RDI’s free online HIV Treatment Response Prediction System (HIV-TRePS) has been re-designed to work on mobile devices such as mobile phones and tablets and at super-fast speed. Users simply log-in via their usual browser and the user interface automatically resizes for their particular mobile device.

HIV-TRePS uses machine learning from tens of thousands of HIV patients treated by hundreds of physicians around the world to predict how an individual patient will respond to any combination of HIV drugs. The new mobile version enables physicians to access this tool on the move, such as during ward rounds, home visits, clinical meetings and even while travelling – anywhere with at least a 3G phone signal available.

The system has also been optimised for processing speed, with the average time to run a case (over broadband) reduced from up to a minute to around 10 seconds.

Sign In or Register now at: https://www.hivrdi.org/treps

Read the full press release here: https://www.hivrdi.org/hiv-treps-on-the-move-press-release-69.htm
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The testing of the RDI’s models as predictors of treatment response with data from the Phidisa cohort in South Africa have been published in the South African Journal of HIV Medicine.
 
The 402 patients in the cohort were changing therapy due to virological failure or toxicity, mostly from 1st to 2nd line regimens. The models, which do not require a genotype for their predictions, were used to predict whether or not the new regimen introduced in the clinic would achieve virological suppression or not.

The models achieved accuracy (area under the receiver-operator curve) of 0.72 compared with 0.80 for a global test set and typically 0.55-0.60 for genotyping with rules based interpretation. They were able to identify alternative, available 3-drug regimens that were predicted to achieve virological suppression in 62% of the cases where the new regimen introduced in the clinic failed.

The predictive accuracy of the models for these South African patients together with the results of previous studies suggest that HIV-TRePS has the potential to optimise treatment selection and reduce virological failure in different patient populations in resource-limited settings, without the use of a genotype.

The paper itself can be found here:

http://sajhivmed.org.za/index.php/hivmed/article/view/450

We hope you find the paper interesting and that you will alert your colleagues and contacts, particularly those in resource-limited settings, to the existence and potential utility of HIV-TRePS.

Sign In or Register now at: https://www.hivrdi.org/treps
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The RDI’s latest models were published this week in the journal of Antimicrobial Chemotherapy.

In all three sets of models are described:

1. Global models that do not require a genotype to make their predictions of HIV treatment response

2. Local models that do not require genotype, trained with data form South Africa only

3. Global models that do require a genotype to make their predictions of HIV treatment response

The main findings were:

1. The global models were highly accurate in their predictions of virological response

2. The global models that do not require a genotype were as accurate for patients from South Africa as the local models trained with only South African data and significantly better than the local models at identifying alternative potentially effective combinations of drugs for patients who failed on the new regimen in the clinic

3. The global models, even those that do not use a genotype, were significantly more accurate than genotyping with rules-based interpretation.

4. The global models that require a genotype to make their predictions were marginally but not statistically significantly more accurate in their predictions of response than the models that do NOT require a genotype

The results provide further evidence that these models, freely available via HIV-TRePS have the potential to improve outcomes through optimised and individualised therapy, particularly in settings where genotyping is not available.

The RDI’s press release can be found here:

http://www.hivrdi.org/most-effective-models-to-date-for-predicting-hiv-treatment-responses-now-published-in-major-journal-press-release-66.htm

The paper itself can be found here:

http://jac.oxfordjournals.org/content/early/2016/06/20/jac.dkw217.abstract?sid=3e6b797a-f14c-41c6-9924-bbc697fdd47d

We hope you find the paper interesting and that you will alert your colleagues and contacts, particularly those in resource-limited settings, to the existence and potential utility of HIV-TRePS.

Sign In or Register now at: https://www.hivrdi.org/treps

The RDI team.
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HIV-TRePS just got even better

Latest models for predicting response to HIV therapy the most accurate to date.
 
LONDON, UK Tuesday 16th February 2016. The RDI’s free online HIV Treatment Response Prediction System (HIV-TRePS) has been updated with the most accurate models to date. Two new sets of models have been developed to predict virological response to any combination of HIV drugs for patients failing on their current therapy.
 
The first set of models was trained using the treatment history, viral load and CD4 count from almost 30,000 patients.  Critically they do not need the results of a resistance test for their predictions, and so are well-suited for use in low- middle-income countries where such tests are not generally affordable.  These ‘global’ models achieved accuracy* of 0.82 in independent testing.  Their performance was compared with that of ‘local’ models trained using data from South African patients only for patients in that country and the global models were found to be superior in terms of their ability to identify alternative combinations of locally-available drugs that were predicted to be effective.
 
“Use of these latest models has the potential to reduce virological failure and improve patient outcomes, particularly in resource-limited settings”, commented Dr Andrew Revell, Executive Director of the RDI.   “The models provide clinicians with a practical tool to support optimised treatment decision-making, even in the absence of resistance tests and where expertise may be lacking in the context of a public health approach to antiretroviral roll-out and management.”
 
The second set of models was developed using 15,130 cases where a genotypic resistance test was obtained while the patient’s therapy was failing, to help inform the selection of the next regimen.  These models achieved accuracy of 0.84 in independent testing.  The models were significantly more accurate predictors of response than the results of the resistance tests, interpreted using the most commonly used interpretation systems, such as Stanford HIVdb, which achieved accuracy scores of 0.55-0.58.
 
“Once again the RDI models have substantially out-performed genotyping with rules-based interpretation as a means of predicting treatment outcomes” commented Dr Brendan Larder, Scientific Chair.  “The results, particularly those from our models that do not require a resistance test, add to the substantial body of evidence suggesting that, where resources are scarce, they would be better allocated to expanding access to treatment rather than resistance testing”.
 
The RDI is an independent, not-for-profit research group set-up in 2002 with the mission to improve the clinical management of HIV infection through the application of bioinformatics to HIV drug resistance and treatment outcome data. Over the thirteen years since its inception, the RDI has worked with many of the leading clinicians and scientists in the world to develop the world’s largest database of HIV drug resistance and treatment outcome data, containing information from approximately 180,000 patients in more than 30 countries.
 
Notes:
HIV-TRePS is an experimental system intended for research use only. The predictions of the system are not intended to replace professional medical care and attention by a qualified medical practitioner and consequently the RDI does not accept any responsibility for the selection of drugs, the patient's response to treatment or differences between the predictions and patients’ responses.

This project has been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261200800001E.  This research was supported by the National Institute of Allergy and Infectious Diseases. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.
 
More information can be found at: www.hivrdi.org.

For further information contact:

Andrew Revell (Executive Director, RDI) on +44 207 226 7314, +44 7067 126498 (mobile) or andrewrevell@hivrdi.org
 
The following are available for interview on request, arranged through Andrew Revell above:

Dr Brendan Larder: Scientific Chairman of the RDI, London, UK
Dr Andrew Revell: Executive Director, RDI, London, UK.
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TRePS users you may have noticed we now email you your TRePS reports upon completion.

We hope you find this new functionality useful, if not, don’t worry you can always turn off the emailing functionality from within TRePS on the ‘My Account’ page.
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We are pleased to announce the launch of our new web site.

The site has had a complete re-design but still includes all the information about the RDI that you might want including, of course, entry to the renowned HIV Treatment Response Prediction System, HIV-TRePS.

The new web site is at the same URL and can be accessed directly from here: http://www.hivrdi.org/

The web site also features for the first time a series of video interviews with our colleagues and research partners at the Chelsea and Westminster Hospital.

Many thanks to Professor Brian Gazzard, Dr Anton Pozniak and Dr Mark Nelson for giving up their valuable time to be filmed. There are also video interviews and conference presentations featuring Brendan Larder, Scientific Chair of the RDI, and Andrew Revell its Executive Director.

The full range of videos can be found here: http://www.hivrdi.org/videos.htm
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Read the article "Predicting response to HIV Therapy" with Brendan Larder in Future Virology.

http://www.hivrdi.org/pdf/future-virology-brendan-larder-interview.pdf
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