Bell Eapen MD, PhD.

Bringing Digital health & Gen AI research to life!

Psoriasis support : eHealth gaming tools for patient engagement

Psoriasis manum
Psoriasis manum (Photo credit: Wikipedia)

Here is the IFPA  survey to compare 17 different strategies and activities that can be used to advance psoriasis education, advocacy and awareness. Preliminary results of the survey will be presented on World Psoriasis Day and the final results will be announced at the 4th World Psoriasis & Psoriatic Arthritis Conference in Stockholm July 8-11, 2015.

I have listed below some of my random ideas on eHealth tools for patient engagement in psoriasis:

An Agent based model (ABM) offers visual simulations of complex systems that can be displayed on a web browser. Psoriasis disease process can be modelled using psoriasis patients as ‘turtles’ with the known probabilities of auto-remission, exacerbation, response to conventional treatments and response to newer drugs added to the model. The patients and caregivers could interact with the model to understand how the treatment decisions affect the quality of life. ABM could be an innovative and useful web based patient education tool that portrays the reality of psoriasis without giving any false promises. Those in the  patient’s circle of care and the patient would understand the odds of improving quality of life.

Psoriasis: The naked truth
Psoriasis: The naked truth (Photo credit: SomosMedicina)

An android or iPhone app to calculate and log the PASI score of the patient would be a less obtrusive disease monitoring tool. The app may be designed to send the log to patient’s caregiver. I have not checked the apple app store or google play, probably such apps already exist.

A ‘push’ strategy such as email alerts is unlikely to work for psoriatics. An innovative strategy game where the body is modelled as a kingdom and the immunological perturbations as a t-cell mutiny could be a useful engagement tool. Vascular and systemic changes could also be part of the game. The game would be web based and would continue for a long time with the patient required to login periodically to make strategic alterations (treatment choices). Everytime the patient login to the game, medication reminders would be displayed. The game would mimic reality with changes reflecting new clinical studies. New clinical studies that has an impact on the ‘game plan’ would be available under the ‘game resources’ for everyone to read. Reading and understanding these resources would improve the performance in the game.

Clinical trials in cosmetic dermatology

Dr. Philip C Anderson in Dermatology Departmen...
Dr. Philip C Anderson in Dermatology Department circa 1967 (Photo credit: Wikipedia)

We are again having an interesting discussion on new generation hairloss treatments in the Dermatologists Sans Borders facebook group. We have discussed about the inconsistencies in the claims of the so called biomimetic peptides before.(Beauty born out of Bioinformatics) So we will not go back into that again. One of the senior members pointed out the two fundamental limitations in conducting a proper clinical trial in a non-critical intervention like hairloss remedies. Cost and time. So this post is basically to explore the challenges and the probable solution in this scenario. I am not a subject expert and the intention is just to offer few breadcrumbs from other fields to ignite thinking amongst this group.

Historical control data:[1]
Historical control data consists of a wide range of data gathered from diverse experiments performed under widely differing conditions. Though historical control data is not as reliable as concurrent controls, it may suffice in this situation as the intervention is non-critical. Use of historical control data may significantly reduce the overall trial costs.

Single-Subject design:
Single-subject design is a research design in which the subject serves as his/her own control, and is sensitive to individual organism differences important in cosmetic interventions. It may also reduce the interpretation bias and reduce the time required to arrive at a preliminary conclusion.

Equivalence / Non-inferiority trials:[2]
Equivalence trials are designed to demonstrate that one treatment is as effective as another. This is especially important here as exotic and expensive treatments bust into the scene all the time. In my cynical view, most of these interventions may not even clear a non-inferiority trial

Systematically reviewing and synthesising evidence from conversation analysis.
This is a new concept that is emerging and may become more and more significant in the new digital age of social networking. To quote from an article in BMC Medical Research Methodology:

Healthcare delivery is largely accomplished in and through conversations between people, and healthcare quality and effectiveness depend enormously upon the communication practices employed within these conversations. An important body of evidence about these practices has been generated by conversation analysis and related discourse analytic approaches, but there has been very little systematic reviewing of this evidence.

Parry, RH. “Systematically reviewing and synthesizing evidence from …” 2013. <>

The Dermatologists sans Borders facebook group was used as a cohort for research couple of years back. Hope this strictly curated group of dermatologists contribute to the corpora of knowledge by active discussions like this.

1. Haseman, Joseph K. “Data analysis: Statistical analysis and use of historical control data.” Regulatory Toxicology and Pharmacology 21.1 (1995): 52-59.
2. D’Agostino, Ralph B, Joseph M Massaro, and Lisa M Sullivan. “Non‐inferiority trials: design concepts and issues–the encounters of academic consultants in statistics.” Statistics in medicine 22.2 (2003): 169-186.

Combining Clinical Trials

English: Icon representing Bayesian statistics
English: Icon representing Bayesian statistics (Photo credit: Wikipedia)

BMC Medical Research Methodology | Abstract | Bayesian methods in clinical trials: a Bayesian analysis of ECOG trials E1684 and E1690:

Happy new year to all!

I have always wondered how to effectively combine data from a previous similar clinical trial into a new trial. If this is not attempted, the wealth of information already collected will be wasted. Besides if the trials give conflicting results, the entire effort in conducting both trials is lost and you end up with only confusion. The authors here have conceived a method to effectively combine data from similar trials conducted at different times using the Bayesian method. In short, the older trial is used to generate the prior probability distribution for the analysis of the new results. The methodology has been used in Melanoma studies. (I am happy that it is from my domain). I have also experimented with Bayesian methodology before.

I give 4 peels to this idea. (Pardon me for using a grading system envisaged for a different cause!) peel rating
My Rating: 4 peels
What is peel score?