Research Statistical Analysis of Wound Healing Rates

A meta-analytical review of wound healing studies showed in large part that prognostic factors for wound closure, to a noticeable extent, were inaccurate in that endpoint utilized in all cases was time to 100% closure. Since many wounds do not ultimately heal completely, a new model was developed in conjunction with Sylvan Wallenstein, Ph.D., Associate Professor of Community and Preventive Medicine in the Mount Sinai School of Medicine.¹⁰⁹

The key parameter in the formulation of a new statistical model for wound healing analysis is wound size rather than time to closure. The reason for this is that in the wound healing process, wound closure is not a necessary endpoint within a fixed time period. Closure may occur within a relatively short time frame or, conversely, rather than progression to closure, the wound may grow in size in an unpredictable manner, thus rendering the concept of time to closure unwieldy. The real question that should be addressed in this context is not really what is the time to closure, but instead, what is the rate of healing?

Thus, the model created for statistical analysis was wound size measured against time, with the observational parameter being reduction in size as indicative of healing. Two-dimensional area of the wound was utilized in the model rather than volume, which poses measurement problems. Planimetry was used to calculate area rather than digital videometry; the latter can be less cost effective and more unwieldy.

To be effective, the model must apply to all categories of wounds—those that heal and those that do not heal, regardless of timeframe. It should also be applicable to small wounds that have the potential to grow unpredictably in size. Additionally, it would be important to generate a model that does not provide for a linear relationship between wound size and time. If the correlation between these two parameters were linear, the ultimate outcome would be a negative wound size, which is unworkable. Thus the model posits wound size as decreasing based on a non-exponential, modified Gompertz-type model; size increase would be designated by a negative decrease. The Gompertz-type model allows for individual variability such that specific differences in individual wound behavior—i.e., the closure of one wound, the failure to heal of another—can be accounted for by the model, which neither a linear model nor an exponential model would be able to do.

A significant advantage of this model is that if different therapies are applied to the same type of wound, the model should ideally, and ultimately, be able to predict rate of healing based on similarity of wound type and of treatment. Thus, this modified Gompertz-type model is hypothesized to detect prognostic factors and assess specific therapeutic interventions.