Current Dupuytren triage and treatment result in a potentially large percentage of undocumented patients. Many patients avoid surgical consultation because of rumor, family, or personal experiences with Dupuytren treatment morbidity. Many patients are diagnosed and told not to return until they have developed severe deformity. Many patients change surgeons after consult or treatment, hoping for a better outcome, and are lost to follow-up. Without a biomarker, the variability of disease progression and the lack of data on untreated disease mean that it is impossible for studies of prophylactic treatment to provide statistically meaningful outcome data, even when hundreds of patients are involved.

Only 1 out of 7 patients with Dupuytren Disease can be expected to have the diagnosis documented in their medical records (DiBenedetti et al. 2011a). Dupuytren-specific information such as age of onset, family history of Dupuytren Disease, and Dupuytren Disease-specific quality of life assessment is only documented in patients being evaluated for treatment by surgeons and inconsistently even in this subgroup. Without a Dupuytren-specific survey, simple record review cannot extract details of dynamic relationships such as the timing of Ledderhose appearance, timing of medication use, or other medical events to the individual time line of Dupuytren appearance and progression.

Clinical research is daunting because many variables dynamically influence Dupuytren activity (Fig. 51.3). Dupuytren Disease often has a slow or intermittent progression to the complication of deformity. Dupuytren contracture has great individual variability of presentation and may be confounded by development of secondary pathoanatomy of joints and tendons. We still lack standard assessment of severity or standard definitions of outcome. There are wide variations in treatment technique within each type of procedure. There are wide variations of biologic aggressiveness of patients treated with the same procedure. Finally, the facts that early Dupuytren Disease is not documented in the majority of cases (DiBenedetti et al. 2011a) and that the USA lacks a centralized medical database pose large obstacles to the study of the natural history of disease.

We’ve been using the wrong tools and aiming at the wrong target to change long-term outcomes. Dupuytren contracture is the crime scene, not the criminal. Our goal should be prevention, not salvage. We must move the focus to disease before deformity. This requires a shift of Dupuytren research from surgical disease research models to chronic disease research models (Table 51.1). Dupuytren Disease is a chronic systemic disorder with episodes of contracture activity. Dupuytren contracture is in some ways the least important and least informative aspect of Dupuytren Disease. Surgical research has several distinct features. It is generally organized in a top-down fashion with a set duration and end point. Surgical research usually focuses on anatomy and technique. It often uses procedure-oriented metrics to assess specific outcome metrics over a short-term fixed duration of study. It answers questions such as “how much was the immediate improvement?” or “what complications occurred?” when comparing different procedures or different study groups undergoing the same procedure. Surgical research represents the majority of Dupuytren research publications and provides valuable guidance to refine technical approaches to contracture management. It has done little toward the development of a cure for Dupuytren Disease. Chronic disease research is often structured for exploration rather than refinement. Chronic diseases, by definition, are chronic because they lack effective long-term treatment. Lack of treatment often stems from lack of understanding of disease biology. Chronic disease research begins by surveying the variety and impact of disease to formulate a clinical disease description. This description guides the search for what questions to ask to identify the cause of disease. Chronic disease research is patient guided, focusing on quality of life metrics, identifying subsets of disease severity, and using biomarkers to guide individualized treatment of different disease subsets. It is typically longitudinal, long term, and open ended. This approach has not been previously applied to large-scale Dupuytren research.

One logical stepwise approach would be as follows. This outline is the basis of the International Dupuytren Data Bank (Eaton 2016).

I introduced the technique of needle aponeurotomy to the USA in 2003. As a result, my practice rapidly became a center for this procedure, and I treated nearly 1000 Dupuytren hands each year with this technique. Realizing that this was an opportunity for data collection, I added research-oriented Dupuytren-specific questions to my new patient intake forms using a standard form based on initial telephone interview. In addition to typical Dupuytren demographics, patients were surveyed on novel topics of interest, including quality of life (“how much does Dupuytren interfere with the use of your hands?”), genetic (parental age at the time of the patient’s birth), symptoms of pain and itching in Dupuytren areas, and others. A total of 3396 unique intake records were available for review in electronic format, of which 3120 records satisfied criteria for completeness. I used custom text processing software to create a de-identified spreadsheet of data retrieved from these records. Data trends were analyzed using Watson Analytics (http://​www.​ibm.​com/​analytics/​watson-analytics/​). This provided a basis to explore and troubleshoot data analysis as pilot work for applying chronic disease research tools to the study of Dupuytren Disease. This was a select group of patients with known biases and is not definitive. Many patients had multiple prior Dupuytren treatments, interest in alternative treatment options, and socioeconomic status which allowed them to travel for specialty care. Almost all patients in this group had scheduled their initial evaluation with needle aponeurotomy in mind. The retrospective data from this cohort is presented here to explore relationships, illustrate concepts, and develop recommendations for future prospective clinical research. What follows below is based on this data exploration, which also guided development of the International Dupuytren Data Bank (Eaton 2016).

The demographics of these patients are profiled in Figs. 51.6, 51.7, and 51.8. Men comprised the majority (77 %), with an average age of 64 and an average age of onset of 53. Women represented 23 % of the group, with an average age of 66 and an average age of onset of 56. The majority of patients had a duration of disease between 1 and 10 years. Record review of patients who returned for more procedures years after their first interview demonstrated variability in reported age of onset and recollection of duration since the prior procedure. Recommendation: offset the unreliability of self–reported clinical durations by repeating questions on dates and durations in longitudinal follow–up surveys.