APASI: The bright future of Psoriasis severity assessment has arrived

In order to calculate the PASI, the sum of the severity of these three main changes was multiplied with the numerical value of the areas involved and with the various percentages of the four body areas. These values were then added in order to obtain the PASI.

Fredriksson, T., & Pettersson, U. (1978). Severe Psoriasis – Oral Therapy with a New Retinoid. Dermatology, 157(4), 238–244. doi:10.1159/000250839

The shortfalls of the pen-and-paper PASI

The main goal of PASI is to provide a tool to record data precisely and consistently for routine evaluations and clinical studies. However, it carries a set of problems and limitations.

We found substantial variation [in the results] between experienced and inexperienced physicians using PASI

Richard G. Langley, MD,a and Charles N. Ellis, MDb Halifax, Nova Scotia, and Ann Arbor. Michigan Evaluating psoriasis with Psoriasis Area and Severity Index, Psoriasis Global Assessment, and Lattice System Physician’s Global Assessment

Aside from the inter-observer variation, many physicians have reported that filling up the paper sheet is too tedious and time-consuming and that they fail to implement its use on a day-to-day basis.

Digital calculators: A half-baked solution to the problem

With the advent of basic computation, several digitalized versions of the PASI scoring system were developed, in an attempt to reduce the time wasted in calculations. These online calculators tackle, although inefficiently, just one of the issues the traditional PASI has: While the math is calculated automatically, the doctor still has to fill in the value for each parameter.

This not only still requires the time and attention of the physician, but does nothing to address the multiple issues of lack of objectivity and reproducibility within the PASI system.

How do we know what scoring system is better?

Among the many criteria for rating the quality of outcome measures, some stand out as key to determining whether a scoring system is useful:

• Ease of use: can be applied easily, given constraints of time and money.
• Sensitivity to change: the ability to detect clinically significant changes over time.
• Interobserver reliability: different investigators provide identical results.
• Intra-observer variability: repeated measurements by the same investigator provide identical results.
• Interpretability: assigns qualitative meaning to scores (mild, severe…).

Methods and definitions to rate the quality of outcome measures. Schmitt, J., Langan, S., Deckert, S., Svensson, A., von Kobyletzki, L., Thomas, K., & Spuls, P. (2013). Assessment of clinical signs of atopic dermatitis: A systematic review and recommendation. Journal of Allergy and Clinical Immunology, 132(6), 1337–1347. doi:10.1016/j.jaci.2013.07.008

Six ways in which APASI is better

Legit.Health is the revolutionary Clinical Data and Communication tool for Next-generation dermatologists that triples the empowerment of patients.

After 12 months using Legit.Health, in which we analysed the applicability of the tool at our hospital, we have drawn conclusions that help to propose a new care paradigm in the follow-up of psoriasis.

Dra. Elena Sánchez-Largo, Torrejon Hospital

The purpose of the deep learning algorithms is to relieve doctors from the tedious manual calculation of scoring systems and allow the practice of more objective evidence-based dermatology while speeding up the pathology reporting process and increasing patients’ autonomy and control.

Legit.Health‘s algorithms automatically grade lesions just by looking at smartphone images and small patient-reported outcome measures (PROMs). In other words: the tool will automatically fill in most of the dermatology scoring systems, such as PASI, SCORAD, UAS, GAGS, and many more.

The main goal of APASI is to provide a tool to record data precisely and consistently for routine evaluations and clinical studies.

	Pen and Paper	Digital	Automatic AI
Self-supervision	–	–	Perform diagnosis
Ease of use	≈ 600 seconds	≈ 420 seconds	≈ 23 seconds
Sensitivity to change	0 to 4	0 to 4	0 to 100
Interobserver variability	Medium (20%)	Medium (20%)	Lowest (8%)
Intra-observer variability	High	High	Zero

1. APASI will assist the doctor in the diagnosis of the disease

The algorithm developed by Legit.Health isn’t limited to measuring the severity of the condition as the PASI does, it also has been trained using the input of top dermatologists to distinguish between 232 pathologies, including most types of psoriasis. 

This means that APASI will distinguish between several types of psoriasis and assist the doctor in the disease assessment process, not only making it quicker by providing relevant information but improving the rate of correct diagnosis by 23%

2. Easier to use and faster than any other existing method

While an experienced physician might take six to seven minutes to completely fill in and calculate the PASI score of a patient, an inexperienced one will need ten minutes. Meanwhile, Legit.Health‘s algorithm only takes 23 seconds to get the final score.

This is key both from a time management perspective, allowing the doctors better use their time with the patient, and from a clinical perspective. The fact that many physicians won’t fill in any scoring system for considering the process too tedious and time-consuming and would rather make a gut estimate of the severity of the disease is incompatible with the modern idea of practising evidence-based medicine.

3. APASI can detect small changes in the evolution of the pathology

Legit.Health‘s tool analyzes the pathologies using a validated scoring system that has both the lowest MID (Minimal important Difference) and is sensible to the lowest LDC (Lowest Detectable Change), which means the algorithm analyzes every image with more precision and attention to detail than any human observer would.

In clinical trials, quantification of the disease is critical to measure the efficacy of an investigational treatment by comparing the severity of disease before therapy to that measured after treatment.

Richard G. Langley, MD,a and Charles N. Ellis, MDb Halifax, Nova Scotia, and Ann Arbor, Michigan Evaluating psoriasis with Psoriasis Area and Severity Index, Psoriasis Global Assessment, and Lattice System Physician’s Global Assessment

Furthermore, it has a higher validity and reliability while maintaining comparable clinimetric properties, thanks to the intrinsic functioning of computer vision algorithms. 

4. Greatly reduces inter-observer variability

Our data indicate that even experienced investigators had difficulty with PASI in rating the area of involvement […], especially among patients with more severe psoriasis.

Richard G. Langley, MD,a and Charles N. Ellis, MDb Halifax, Nova Scotia, and Ann Arbor, Michigan Evaluating psoriasis with Psoriasis Area and Severity Index, Psoriasis Global Assessment, and Lattice System Physician’s Global Assessment

The experimental results show that APASI outperforms the baseline methods when it comes to inter-observer variability, achieving a mean absolute percentage of error of just 13%, way below the usual 20% that can be observed in the classical application of the traditional scoring systems.

5. Zero Intra-observer variability thanks to APASI

The algorithm nature of the APASI eliminates entirely and without doubt, the intra-observer variability, as every image and calculation is stored in the app’s database.

Allowing the doctor to not rely on his memory when assessing the severity of the affection and focusing on the analysis of the objective data stored in the app reduces considerably the risk of misremembering, providing a more objective, accurate, and precise way of tracing the development of the disease.

To judge a treatment effect, the variation in rating a patient from time to time should be low

Richard G. Langley, MD,a and Charles N. Ellis, MDb Halifax, Nova Scotia, and Ann Arbor, Michigan Evaluating psoriasis with Psoriasis Area and Severity Index, Psoriasis Global Assessment, and Lattice System Physician’s Global Assessment

This becomes especially important in clinical trials, where reducing this kind of variability is key to gathering the precise data required in this kind of study.

6. More accessible and easier-to-read data

Last but not least, Legit.Health‘s interface provides access to all the relevant information about the patient in an easy-to-read manner.

Every data derived from the APASI is clearly displayed on the screen, showing the severity of the affection and the different factors considered by the algorithm when analyzing the image and their scores.

The app also provides a handy graff that shows the evolution of the disease across time and makes following the healing process and the effectiveness of the treatment really easy.

In conclusion

The revolutionary and innovative APASI represents the future of dermatology. We are giving doctors access to the best tool for the diagnosis of psoriasis and allowing them to practice evidence-based medicine and improve the communication between doctor and patient.

Thanks to Legit.Health, doctors across the globe can improve their correct diagnosis rate by 23% and make treatment easier to follow for the patient by making them active participants in their own recovery.

There is no denying that the use of algorithms that estimate the severity of the disease represents a bright future for the practice of dermatology and that will, without doubt, help advance the field.