Research Award Details

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Long‐Term (> 10 year) Assessment of Outcomes from Surgical Treatment of Early Onset Scoliosis: Development of Methodology and Outcome Assessment Tools

Grant Recipient: Jeffrey Sawyer, MD

University of Tennessee-Campbell Clinic
Presentations & Publications:
Further Funding:
Additional Information:
POSNA Final Report: Long‐Term (> 10 year) Assessment of Outcomes from Surgical Treatment of Early Onset Scoliosis: Development of Methodology and Outcome Assessment Tools
Jeffrey Sawyer MD:  University of Tennessee-Campbell Clinic
Early Onset Scoliosis (EOS) is a complex condition affecting children younger than 10 that is characterized by spinal deformity, oftentimes severe, which can be fatal if left untreated [1, 2]. Severe spinal deformity leads to pulmonary hypertension and cor pulmonale, and early treatment of progressive curves is vital to preserving cardiopulmonary function [3].
Two significant voids in EOS research are the lack of long‐term follow‐up data on patients and the use of patient-reported outcome measures. Despite the fact that considerable information exists in terms of the surgical treatment of EOS, very little is known about how surgically-treated EOS patients are doing in adulthood in terms of their spinal and pulmonary function and socially in terms of employment, independent living, and marriage. Moreover, locating patients after a long period of no contact poses a challenge, due to patient relocation, name changes, and mortality. Thus, the following primary outcome measurements of success were created: 
  1. The evaluation and development of optimal validated self-reported outcome scores to be used in long-term follow-up studies of EOS patients.
  2. The development of an optimal, literature-based, standardized patient contact information collection method to be used in long-term follow-up studies.
  3. To apply these measures to obtain a patient response rate > 40%.

Project milestones of developing a patient search algorithm using evidenced-based practices in orthopaedic literature and compiling a patient survey using validated patient-reported outcome measurements of health-related quality of life were achieved. Demographic questions used in scholarly publications were also included in the survey. To ensure survey selection would provide a suitable and comprehensive assessment of this patient population, input was sought from experts in pediatric orthopaedics and pulmonology. In addition to Campbell Clinic, eight sites elected to participate in this study. Revisions to the patient survey based on expert feedback as well as inclusion of sites to this study required additional IRB applications, which extended the timeline to contacting patients; however, these modifications should allow for a deeper insight into EOS patient outcomes and provide greater statistical power for data analysis. At this time, IRB applications have been submitted at all sites, most sites have received IRB approval, and multiple sites have received completed patient surveys.  

The validated patient reported outcome measures selected were the SRS-22, SF-12, and FACIT-Dyspnea questionnaires.

  • SRS-22 is the most widely used measure for evaluating health-related quality of life (HRQOL) in patients with and without scoliosis [4] and has been validated in the adolescent and adult populations [5]. SRS-22 is the only scale that successfully assesses comprehensive domains of HRQOL in patients with scoliosis from age 9 years through adulthood [6].
  • The SF-12 is a generic questionnaire administered to assess the physical and mental condition of patients and one of the most widely used instruments for assessing self-reported HRQOL [7]. The SF-12 has been used in scoliosis research with SRS-22 [8]. It is recommended that both generic and disease-specific HRQOL measures be administered for a more comprehensive evaluation of the patient’s HRQOL [9].
  • The FACIT-Dyspnea questionnaire is a short form that has been validated for use in evaluating dyspnea and functional limitations in patients with systemic sclerosis [10]. Because both systemic sclerosis and EOS are associated with restrictive lung disease, this instrument was chosen to evaluate this patient population.

At the inception of this project, several challenges were considered that could stand in the way of achieving a 40% response rate including difficulty with locating patients after a long period of no contact and patient willingness to complete a questionnaire once contact has been made. However, literature describing long-term follow-up studies not only indicated that a long interval of no contact may not preclude follow-up [11] but that most patients contacted by mail or phone are willing to complete a questionnaire [12]. The search algorithm for this project (Figure 1) is based on one developed by Louis et al, which was the most recently published systematic search algorithm utilizing web-based people search platforms to locate patients when traditional means of contacting them are unsuccessful, such as using their last known phone number and address from their medical record [11].

The proposed steps included first determining if a patient is deceased by referencing the Social Security Death Index then utilizing White Pages to perform a broad search followed by PeopleFinders to narrow results by cross-referencing identifiers like birthday, next-of-kin, and previous addresses with the patient’s medical record. Utilizing both White Pates and PeopleFinders leveraged their relative strengths, as PeopleFinders effectively compiled a list of previously lived locations while White Pages was superior at providing up-to-date contact information when searches were narrowed based on locations identified using PeopleFinders [11]. This technique allowed Louis et al to successfully find 74% of patients not found previously using medical records after 10 years of no contact resulting in a 92% overall follow-up rate. Adjunct search techniques were added to the search algorithm for this project based on additional recommendations in the literature, such as using Facebook to compile a list of previously lived locations and requesting assistance in patient contact through their primary care physician [13]. The primary care physician’s nursing staff can also help, as patients may exchange holiday cards with staff after moving and sending patient letters through the United States Postal Service can be used to determine if a patient’s address has changed in the previous year [14].

Figure 1: Patient search algorithm

Funding from the POSNA Micro Grant has been used to pay a research assistant and for purchase of study materials (e.g. postage, envelopes) for the multicenter study sites. An expense report for the grant year has been included (Table 1). Once a sufficient number of sites have identified patients lost to follow-up, subscriptions will be purchased for the web-based people search platforms outlined in the search algorithm. Since acceptance of the POSNA Micro Grant and the development of this algorithm, this project has been additionally funded by a grant from DePuy Synthes in the amount of $47,500 over 2 years. Upon completion of this project, it is planned to submit findings to POSNA, SRS, and ICEOS and publication.

It should be noted that using the algorithm developed by this microgrant, data collection has begun at 7 United States institutions with over 50 patients enrolled in the study to date.  This will be the largest series of long term follow up on EOS patients in existence.

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[2] Thorsness RJ, MD, et al. Nonsurgical Management of Early-onset Scoliosis. Journal of the American Academy of Orthopaedic Surgeons 2015; 23: 519-28.
[3] Fernandes P, MD, et al. Natural History of Early Onset Scoliosis. The Journal of Bone and Joint Surgery 2007; 89-A: 21-33.
[4] Caronni A, MD, et al. ISYQOL: a Rasch-consistent questionnaire for measuring health-related quality of life in adolescents with spinal deformities. The Spine Journal 2017; 17: 1364-72.
[5] Theroux J, et al. Revisiting the psychometric properties of the Scoliosis Research Society-22 (SRS-22) French version. Scoliosis and Spinal Disorders 2017; 12:21: 1-7.
[6] Lai S, PhD, MS, MBA, et al. Estimating SRS-22 Quality of Life Measures With SF-36. Spine 2006; 31: 473-8.
[7] Huo T, et al. Assessing the reliability of the short form 12 (SF-12) health survey in adults with mental health conditions: a report from the wellness incentive and navigation (WIN) study. Health and Quality of Life Outcomes 2018; 16(34): 1-8.
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[10] Hinchcliff M, MD, MS, et al. Validity of Two New Patient Reported Outcome Measures in Systemic Sclerosis: the PROMIS-29 Profile and the FACIT- Dyspnea. Arthritis Care Res (Hoboken) 2011; 63(11): 1620-8.
[11] Louie DL, BA, et al. Finding Orthopedic Patients Lost to Follow-up for Long-term Outcomes Research Using the Internet: An Update for 2012. The Cutting Edge 2012; 35: 595-9.
[12] Cooper DM, MD, et al. Treatment of Idiopathic Clubfoot. The Journal of Bone and Joint Surgery 1995; 77-A(10): 1477-89.
[13] Biant LC, et al. How to find patients who are ‘lost to follow-up’. Ann R Coll Surg Engl (Suppl) 2010; 92: 98-101.
[14] Smith JS, MD, et al. Current Concepts Review: Methods for Locating Missing Patients for the Purpose of Long-Term Clinical Studies. The Journal of Bone and Joint Surgery 1998; 80-A(3): 431-8.