Imaging for Early Detection of Pancreatic Ductal Adenocarcinoma: Updates and Challenges in the Implementation of Screening and Surveillance Programs.

Pancreatic ductal adenocarcinoma (PDA) is one of the most aggressive cancers. It has a poor 5-year survival rate of 12%, partly because most cases are diagnosed at advanced stages, precluding curative surgical resection. Early-stage PDA has significantly better prognoses due to increased potential for curative interventions, making early detection of PDA critically important to improved patient outcomes. We examine current and evolving early detection concepts, screening strategies, diagnostic yields among high-risk individuals, controversies, and limitations of standard-of-care imaging.

Sotorasib Is a Pan-RASG12C Inhibitor Capable of Driving Clinical Response in NRASG12C Cancers.

KRASG12C inhibitors, like sotorasib and adagrasib, potently and selectively inhibit KRASG12C through a covalent interaction with the mutant cysteine, driving clinical efficacy in KRASG12C tumors. Because amino acid sequences of the three main RAS isoforms-KRAS, NRAS, and HRAS-are highly similar, we hypothesized that some KRASG12C inhibitors might also target NRASG12C and/or HRASG12C, which are less common but critical oncogenic driver mutations in some tumors. Although some inhibitors, like adagrasib, were highly selective for KRASG12C, others also potently inhibited NRASG12C and/or HRASG12C. Notably, sotorasib was five-fold more potent against NRASG12C compared with KRASG12C or HRASG12C. Structural and reciprocal mutagenesis studies suggested that differences in isoform-specific binding are mediated by a single amino acid: Histidine-95 in KRAS (Leucine-95 in NRAS). A patient with NRASG12C colorectal cancer treated with sotorasib and the anti-EGFR antibody panitumumab achieved a marked tumor response, demonstrating that sotorasib can be clinically effective in NRASG12C-mutated tumors. SIGNIFICANCE: These studies demonstrate that certain KRASG12C inhibitors effectively target all RASG12C mutations and that sotorasib specifically is a potent NRASG12C inhibitor capable of driving clinical responses. These findings have important implications for the treatment of patients with NRASG12C or HRASG12C cancers and could guide design of NRAS or HRAS inhibitors. See related commentary by Seale and Misale, p. 698. This article is featured in Selected Articles from This Issue, p. 695.

Cancer Diagnoses After Recent Weight Loss.

Importance: Weight loss is common in primary care. Among individuals with recent weight loss, the rates of cancer during the subsequent 12 months are unclear compared with those without recent weight loss. Objective: To determine the rates of subsequent cancer diagnoses over 12 months among health professionals with weight loss during the prior 2 years compared with those without recent weight loss. Design, Setting, and Participants: Prospective cohort analysis of females aged 40 years or older from the Nurses' Health Study who were followed up from June 1978 until June 30, 2016, and males aged 40 years or older from the Health Professionals Follow-Up Study who were followed up from January 1988 until January 31, 2016. Exposure: Recent weight change was calculated from the participant weights that were reported biennially. The intentionality of weight loss was categorized as high if both physical activity and diet quality increased, medium if only 1 increased, and low if neither increased. Main Outcome and Measures: Rates of cancer diagnosis during the 12 months after weight loss. Results: Among 157 474 participants (median age, 62 years [IQR, 54-70 years]; 111 912 were female [71.1%]; there were 2631 participants [1.7%] who self-identified as Asian, Native American, or Native Hawaiian; 2678 Black participants [1.7%]; and 149 903 White participants [95.2%]) and during 1.64 million person-years of follow-up, 15 809 incident cancer cases were identified (incident rate, 964 cases/100 000 person-years). During the 12 months after reported weight change, there were 1362 cancer cases/100 000 person-years among all participants with recent weight loss of greater than 10.0% of body weight compared with 869 cancer cases/100 000 person-years among those without recent weight loss (between-group difference, 493 cases/100 000 person-years [95% CI, 391-594 cases/100 000 person-years]; P < .001). Among participants categorized with low intentionality for weight loss, there were 2687 cancer cases/100 000 person-years for those with weight loss of greater than 10.0% of body weight compared with 1220 cancer cases/100 000 person-years for those without recent weight loss (between-group difference, 1467 cases/100 000 person-years [95% CI, 799-2135 cases/100 000 person-years]; P < .001). Cancer of the upper gastrointestinal tract (cancer of the esophagus, stomach, liver, biliary tract, or pancreas) was particularly common among participants with recent weight loss; there were 173 cancer cases/100 000 person-years for those with weight loss of greater than 10.0% of body weight compared with 36 cancer cases/100 000 person-years for those without recent weight loss (between-group difference, 137 cases/100 000 person-years [95% CI, 101-172 cases/100 000 person-years]; P < .001). Conclusions and Relevance: Health professionals with weight loss within the prior 2 years had a significantly higher risk of cancer during the subsequent 12 months compared with those without recent weight loss. Cancer of the upper gastrointestinal tract was particularly common among participants with recent weight loss compared with those without recent weight loss.

Body Composition, Coronary Microvascular Dysfunction, and Future Risk of Cardiovascular Events Including Heart Failure.

BACKGROUND: Body mass index (BMI) is a controversial marker of cardiovascular prognosis, especially in women. Coronary microvascular dysfunction (CMD) is prevalent in obese patients and a better discriminator of risk than BMI, but its association with body composition is unknown. OBJECTIVES: The authors used a deep learning model for body composition analysis to investigate the relationship between CMD, skeletal muscle (SM), subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT), and their contribution to adverse outcomes in patients referred for evaluation of coronary artery disease. METHODS: Consecutive patients (n = 400) with normal perfusion and preserved left ventricular ejection fraction on cardiac stress positron emission tomography were followed (median, 6.0 years) for major adverse events, including death and hospitalization for myocardial infarction or heart failure. Coronary flow reserve (CFR) was quantified as stress/rest myocardial blood flow from positron emission tomography. SM, SAT, and VAT cross-sectional areas were extracted from abdominal computed tomography at the third lumbar vertebra using a validated automated algorithm. RESULTS: Median age was 63, 71% were female, 50% non-White, and 50% obese. Compared with the nonobese, patients with obesity (BMI: 30.0-68.4 kg/m2) had higher SAT, VAT, and SM, and lower CFR (all P < 0.001). In adjusted analyses, decreased SM but not increased SAT or VAT was significantly associated with CMD (CFR <2; OR: 1.38; 95% CI: 1.08-1.75 per -10 cm2/m2 SM index; P < 0.01). Both lower CFR and SM, but not higher SAT or VAT, were independently associated with adverse events (HR: 1.83; 95% CI: 1.25-2.68 per -1 U CFR and HR: 1.53; 95% CI: 1.20-1.96 per -10 cm2/m2 SM index, respectively; P < 0.002 for both), especially heart failure hospitalization (HR: 2.36; 95% CI: 1.31-4.24 per -1 U CFR and HR: 1.87; 95% CI: 1.30-2.69 per -10 cm2/m2 SM index; P < 0.004 for both). There was a significant interaction between CFR and SM (adjusted P = 0.026), such that patients with CMD and sarcopenia demonstrated the highest rate of adverse events, especially among young, female, and obese patients (all P < 0.005). CONCLUSIONS: In a predominantly female cohort of patients without flow-limiting coronary artery disease, deficient muscularity, not excess adiposity, was independently associated with CMD and future adverse outcomes, especially heart failure. In patients with suspected ischemia and no obstructive coronary artery disease, characterization of lean body mass and coronary microvascular function may help to distinguish obese phenotypes at risk for cardiovascular events.

Accelerating artificial intelligence: How federated learning can protect privacy, facilitate collaboration, and improve outcomes.

Cross-institution collaborations are constrained by data-sharing challenges. These challenges hamper innovation, particularly in artificial intelligence, where models require diverse data to ensure strong performance. Federated learning (FL) solves data-sharing challenges. In typical collaborations, data is sent to a central repository where models are trained. With FL, models are sent to participating sites, trained locally, and model weights aggregated to create a master model with improved performance. At the 2021 Radiology Society of North America's (RSNA) conference, a panel was conducted titled "Accelerating AI: How Federated Learning Can Protect Privacy, Facilitate Collaboration and Improve Outcomes." Two groups shared insights: researchers from the EXAM study (EMC CXR AI Model) and members of the National Cancer Institute's Early Detection Research Network's (EDRN) pancreatic cancer working group. EXAM brought together 20 institutions to create a model to predict oxygen requirements of patients seen in the emergency department with COVID-19 symptoms. The EDRN collaboration is focused on improving outcomes for pancreatic cancer patients through earlier detection. This paper describes major insights from the panel, including direct quotes. The panelists described the impetus for FL, the long-term potential vision of FL, challenges faced in FL, and the immediate path forward for FL.

Adipose tissue and skeletal muscle wasting precede clinical diagnosis of pancreatic cancer.

Patients with pancreatic cancer commonly develop weight loss and muscle wasting. Whether adipose tissue and skeletal muscle losses begin before diagnosis and the potential utility of such losses for earlier cancer detection are not well understood. We quantify skeletal muscle and adipose tissue areas from computed tomography (CT) imaging obtained 2 months to 5 years before cancer diagnosis in 714 pancreatic cancer cases and 1748 matched controls. Adipose tissue loss is identified up to 6 months, and skeletal muscle wasting is identified up to 18 months before the clinical diagnosis of pancreatic cancer and is not present in the matched control population. Tissue losses are of similar magnitude in cases diagnosed with localized compared with metastatic disease and are not correlated with at-diagnosis circulating levels of CA19-9. Skeletal muscle wasting occurs in the 1-2 years before pancreatic cancer diagnosis and may signal an upcoming diagnosis of pancreatic cancer.

Oncogenic Drivers and Therapeutic Vulnerabilities in KRAS Wild-Type Pancreatic Cancer.

PURPOSE: Approximately 8% to 10% of pancreatic ductal adenocarcinomas (PDAC) do not harbor mutations in KRAS. Understanding the unique molecular and clinical features of this subset of pancreatic cancer is important to guide patient stratification for clinical trials of molecularly targeted agents. EXPERIMENTAL DESIGN: We analyzed a single-institution cohort of 795 exocrine pancreatic cancer cases (including 785 PDAC cases) with a targeted multigene sequencing panel and identified 73 patients (9.2%) with KRAS wild-type (WT) pancreatic cancer. RESULTS: Overall, 43.8% (32/73) of KRAS WT cases had evidence of an alternative driver of the MAPK pathway, including BRAF mutations and in-frame deletions and receptor tyrosine kinase fusions. Conversely, 56.2% of cases did not harbor a clear MAPK driver alteration, but 29.3% of these MAPK-negative KRAS WT cases (12/41) demonstrated activating alterations in other oncogenic drivers, such as GNAS, MYC, PIK3CA, and CTNNB1. We demonstrate potent efficacy of pan-RAF and MEK inhibition in patient-derived organoid models carrying BRAF in-frame deletions. Moreover, we demonstrate durable clinical benefit of targeted therapy in a patient harboring a KRAS WT tumor with a ROS1 fusion. Clinically, patients with KRAS WT tumors were significantly younger in age of onset (median age: 62.6 vs. 65.7 years; P = 0.037). SMAD4 mutations were associated with a particularly poor prognosis in KRAS WT cases. CONCLUSIONS: This study defines the genomic underpinnings of KRAS WT pancreatic cancer and highlights potential therapeutic avenues for future investigation in molecularly directed clinical trials. See related commentary by Kato et al., p. 4527.

Potential of artificial intelligence in the risk stratification for and early detection of pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is the third most lethal cancer in the United States, with a 5-year life expectancy of 11%. Most symptoms manifest at an advanced stage of the disease when surgery is no longer appropriate. The dire prognosis of PDAC warrants new strategies to improve the outcomes of patients, and early detection has garnered significant attention. However, early detection of PDAC is most often incidental, emphasizing the importance of developing new early detection screening strategies. Due to the low incidence of the disease in the general population, much of the focus for screening has turned to individuals at high risk of PDAC. This enriches the screening population and balances the risks associated with pancreas interventions. The cancers that are found in these high-risk individuals by MRI and/or EUS screening show favorable 73% 5-year overall survival. Even with the emphasis on screening in enriched high-risk populations, only a minority of incident cancers are detected this way. One strategy to improve early detection outcomes is to integrate artificial intelligence (AI) into biomarker discovery and risk models. This expert review summarizes recent publications that have developed AI algorithms for the applications of risk stratification of PDAC using radiomics and electronic health records. Furthermore, this review illustrates the current uses of radiomics and biomarkers in AI for early detection of PDAC. Finally, various challenges and potential solutions are highlighted regarding the use of AI in medicine for early detection purposes.

A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories.

Pancreatic cancer is an aggressive disease that typically presents late with poor outcomes, indicating a pronounced need for early detection. In this study, we applied artificial intelligence methods to clinical data from 6 million patients (24,000 pancreatic cancer cases) in Denmark (Danish National Patient Registry (DNPR)) and from 3 million patients (3,900 cases) in the United States (US Veterans Affairs (US-VA)). We trained machine learning models on the sequence of disease codes in clinical histories and tested prediction of cancer occurrence within incremental time windows (CancerRiskNet). For cancer occurrence within 36 months, the performance of the best DNPR model has area under the receiver operating characteristic (AUROC) curve = 0.88 and decreases to AUROC (3m) = 0.83 when disease events within 3 months before cancer diagnosis are excluded from training, with an estimated relative risk of 59 for 1,000 highest-risk patients older than age 50 years. Cross-application of the Danish model to US-VA data had lower performance (AUROC = 0.71), and retraining was needed to improve performance (AUROC = 0.78, AUROC (3m) = 0.76). These results improve the ability to design realistic surveillance programs for patients at elevated risk, potentially benefiting lifespan and quality of life by early detection of this aggressive cancer.

Pancreatic cancer is associated with medication changes prior to clinical diagnosis.

Patients with pancreatic ductal adenocarcinoma (PDAC) commonly develop symptoms and signs in the 1-2 years before diagnosis that can result in changes to medications. We investigate recent medication changes and PDAC diagnosis in Nurses' Health Study (NHS; females) and Health Professionals Follow-up Study (HPFS; males), including up to 148,973 U.S. participants followed for 2,994,057 person-years and 991 incident PDAC cases. Here we show recent initiation of antidiabetic (NHS) or anticoagulant (NHS, HFS) medications and cessation of antihypertensive medications (NHS, HPFS) are associated with pancreatic cancer diagnosis in the next 2 years. Two-year PDAC risk increases as number of relevant medication changes increases (P-trend <1 × 10-5), with participants who recently start antidiabetic and stop antihypertensive medications having multivariable-adjusted hazard ratio of 4.86 (95%CI, 1.74-13.6). These changes are not associated with diagnosis of other digestive system cancers. Recent medication changes should be considered as candidate features in multi-factor risk models for PDAC, though they are not causally implicated in development of PDAC.

Body composition and lung cancer-associated cachexia in TRACERx.

Cancer-associated cachexia (CAC) is a major contributor to morbidity and mortality in individuals with non-small cell lung cancer. Key features of CAC include alterations in body composition and body weight. Here, we explore the association between body composition and body weight with survival and delineate potential biological processes and mediators that contribute to the development of CAC. Computed tomography-based body composition analysis of 651 individuals in the TRACERx (TRAcking non-small cell lung Cancer Evolution through therapy (Rx)) study suggested that individuals in the bottom 20th percentile of the distribution of skeletal muscle or adipose tissue area at the time of lung cancer diagnosis, had significantly shorter lung cancer-specific survival and overall survival. This finding was validated in 420 individuals in the independent Boston Lung Cancer Study. Individuals classified as having developed CAC according to one or more features at relapse encompassing loss of adipose or muscle tissue, or body mass index-adjusted weight loss were found to have distinct tumor genomic and transcriptomic profiles compared with individuals who did not develop such features. Primary non-small cell lung cancers from individuals who developed CAC were characterized by enrichment of inflammatory signaling and epithelial-mesenchymal transitional pathways, and differentially expressed genes upregulated in these tumors included cancer-testis antigen MAGEA6 and matrix metalloproteinases, such as ADAMTS3. In an exploratory proteomic analysis of circulating putative mediators of cachexia performed in a subset of 110 individuals from TRACERx, a significant association between circulating GDF15 and loss of body weight, skeletal muscle and adipose tissue was identified at relapse, supporting the potential therapeutic relevance of targeting GDF15 in the management of CAC.

Postoperative surveillance of pancreatic ductal adenocarcinoma (PDAC) recurrence: practice pattern on standardized imaging and reporting from the society of abdominal radiology disease focus panel on PDAC.

PURPOSE: Surgical resection is the only potential curative treatment for patients with pancreatic ductal adenocarcinoma (PDAC), but unfortunately most patients recur within 5 years of surgery. This article aims to assess the practice patterns across major academic institutions and develop consensus recommendations for postoperative imaging and interpretation in patients with PDAC. METHODS: The consensus recommendations for postoperative imaging surveillance following PDAC resection were developed using the Delphi method. Members of the Society of Abdominal Radiology (SAR) PDAC Disease Focused Panel (DFP) underwent three rounds of surveys followed by live webinar group discussions to develop consensus recommendations. RESULTS: Significant variations currently exist in the postoperative surveillance of PDAC, even among academic institutions. Differentiating common postoperative inflammatory and fibrotic changes from tumor recurrence remains a diagnostic challenge, and there is no reliable size threshold or growth rate of imaging findings that can provide differentiation. A new liver lesion or peritoneal nodule should be considered suspicious for tumor recurrence, and the imaging features should be interpreted in the appropriate clinical context (e.g., CA 19-9, clinical presentation, pathologic staging). CONCLUSION: Postoperative imaging following PDAC resection is challenging to interpret due to the presence of confounding postoperative inflammatory changes. A standardized reporting template for locoregional findings and report impression may improve communication of relaying risk of recurrence with referring providers, which merits validation in future studies.

Utility of Normalized Body Composition Areas, Derived From Outpatient Abdominal CT Using a Fully Automated Deep Learning Method, for Predicting Subsequent Cardiovascular Events.

BACKGROUND. CT-based body composition (BC) measurements have historically been too resource intensive to analyze for widespread use and have lacked robust comparison with traditional weight metrics for predicting cardiovascular risk. OBJECTIVE. The aim of this study was to determine whether BC measurements obtained from routine CT scans by use of a fully automated deep learning algorithm could predict subsequent cardiovascular events independently from weight, BMI, and additional cardiovascular risk factors. METHODS. This retrospective study included 9752 outpatients (5519 women and 4233 men; mean age, 53.2 years; 890 patients self-reported their race as Black and 8862 self-reported their race as White) who underwent routine abdominal CT at a single health system from January 2012 through December 2012 and who were given no major cardiovascular or oncologic diagnosis within 3 months of undergoing CT. Using publicly available code, fully automated deep learning BC analysis was performed at the L3 vertebral body level to determine three BC areas (skeletal muscle area [SMA], visceral fat area [VFA], and subcutaneous fat area [SFA]). Age-, sex-, and race-normalized reference curves were used to generate z scores for the three BC areas. Subsequent myocardial infarction (MI) or stroke was determined from the electronic medical record. Multivariable-adjusted Cox proportional hazards models were used to determine hazard ratios (HRs) for MI or stroke within 5 years after CT for the three BC area z scores, with adjustment for normalized weight, normalized BMI, and additional cardiovascular risk factors (smoking status, diabetes diagnosis, and systolic blood pressure). RESULTS. In multivariable models, age-, race-, and sex-normalized VFA was associated with subsequent MI risk (HR of highest quartile compared with lowest quartile, 1.31 [95% CI, 1.03-1.67], p = .04 for overall effect) and stroke risk (HR of highest compared with lowest quartile, 1.46 [95% CI, 1.07-2.00], p = .04 for overall effect). In multivariable models, normalized SMA, SFA, weight, and BMI were not associated with subsequent MI or stroke risk. CONCLUSION. VFA derived from fully automated and normalized analysis of abdominal CT examinations predicts subsequent MI or stroke in Black and White patients, independent of traditional weight metrics, and should be considered an adjunct to BMI in risk models. CLINICAL IMPACT. Fully automated and normalized BC analysis of abdominal CT has promise to augment traditional cardiovascular risk prediction models.

Relationships between Running Biomechanics, Hip Muscle Strength, and Running-Related Injury in Female Collegiate Cross-country Runners.

Background: Female collegiate cross-country (XC) runners have a high incidence of running-related injury (RRI). Limited reports are available that have examined potential intrinsic factors that may increase RRI risk in this population. Purpose: To examine the relationships between RRI, hip muscle strength, and lower extremity running kinematics in female collegiate XC runners. Study Design: Prospective observational cohort. Methods: Participants included twenty female NCAA collegiate XC runners from Southern California universities who competed in the 2019-20 intercollegiate season. A pre-season questionnaire was used to gather demographic information. Hip muscle strength was measured with isokinetic dynamometry in a sidelying open-chain position and normalized by the runner's body weight (kg). Running kinematic variables were examined using Qualisys 3D Motion Capture and Visual 3D analysis. RRI occurrence was obtained via post-season questionnaires. Independent t-tests were used to determine mean differences between injured and non-injured runners for hip abductor muscle strength and selected running kinematics. Pearson correlation coefficients were calculated to examine relationships between hip muscle performance and kinematic variables. Results: End-of-the-season RRI information was gathered from 19 of the 20 participants. During the 2019-20 XC season, 57.9% (11 of 19) of the runners sustained an RRI. There were no significant differences between mean hip abductor normalized muscle strength (p=0.76) or mean normalized hip muscle strength asymmetry (p=0.18) of injured and non-injured runners during the XC season. Similarly, no significant differences were found between mean values of selected kinematic variables of runners who did and who did not report an RRI. Moderate relationships were found between hip abductor strength variables and right knee adduction at footstrike (r=0.50), maximum right knee adduction during stance (r=0.55), left supination at footstrike (r=0.48), right peak pronation during stance (r=-0.47), left supination at footstrike (r=0.51), and right peak pronation during stance (r=-0.54) (all p≤0.05). Conclusions: Hip abduction muscle strength, hip abduction strength asymmetry, and selected running kinematic variables were not associated with elevated risk of RRI in female collegiate XC runners.

What Can We Learn About Pancreatic Adenocarcinoma from Imaging?

Imaging and endoscopy play several important roles in the diagnosis and management of pancreatic ductal adenocarcinoma (PDAC). Computed tomography (CT) and endoscopic ultrasound play complimentary roles in the initial diagnosis and pathologic confirmation of PDAC. Endoscopy can also be used to manage biliary obstruction and gastrointestinal complications. MRI and fluorodeoxyglucose-PET-CT are typically used as problem-solving tools for complex cases. Neoadjuvant chemotherapy and surgery are often selected based on imaging findings related to vascular involvement by tumors and invasion of adjacent structures. Posttreatment surveillance imaging is used to monitor for complications, local recurrence, and systemic metastasis.

Prospective Assessment of Clinical Tests Used to Evaluate Tibial Stress Fracture.

Background: Tibial stress fracture (SFx) is the most common SFx of the lower extremity. Presently, diagnostic accuracy of clinical examination techniques for tibial SFx remains suboptimal. Purpose: To assess the diagnostic effectiveness of 5 clinical tests for tibial SFx individually versus a test item cluster. Study Design: Cohort study (diagnosis); Level of evidence, 3. Methods: A total of 50 patients with tibial pain (17 with bilateral symptoms) were assessed with 5 clinical examination tests (tibial fulcrum test, focal tenderness to palpation, heel percussion test, therapeutic ultrasound test, and 128-Hz tuning fork test) before they underwent diagnostic imaging (radionuclide bone scan). The application of the clinical tests was counterbalanced to minimize the likelihood of carryover effects. Patients provided a pain rating immediately before and after the application of each clinical test. Results: The prevalence of tibial SFx among the study participants was 52.2%. High levels of specificity were produced by the therapeutic ultrasound test (93.8%), tuning fork test (90.6%), and percussion test (90.6%). The fulcrum test had moderate to high specificity (84.4%). All tests demonstrated low levels of sensitivity, with the highest levels found for focal tenderness to palpation (48.6%) and fulcrum (45.7%). The fulcrum test provided the highest positive likelihood ratio (2.93), followed by the therapeutic ultrasound test (2.30). The fulcrum test had the lowest negative likelihood ratio (0.64), with the focal tenderness to palpation and tuning fork tests having negative likelihood ratios >1.0. Combinations of these clinical tests did not improve the prediction of tibial SFx above that observed among the individual tests. Conclusion: The clinical tests evaluated were generally highly specific, but all had low sensitivity. The fulcrum test provided the highest level of diagnostic accuracy; however, it was inadequate for definitive clinical management. Combining tests did not improve the diagnostic accuracy of tibial SFx.

Improving Access and Decreasing Healthcare Utilization for Patients With Acute Spine Pain: Five-Year Results of a Direct Access Clinic.

INTRODUCTION: Spine pain is one of the largest and costliest burdens to our healthcare systems. While evidence-based guidelines for spine pain have been established, and continue to evolve, the actual management of this condition continues to burden the healthcare system. This has led to increased costs due to inefficient entry to healthcare, utilization of treatments unsupported by clinical guidelines, and patient navigation through our healthcare systems. The purpose of this study was to assess the healthcare utilization and related outcomes for Active Duty Service Members (ADSM) receiving healthcare services in a novel acute spine pain clinic (ASPC) during the first 5 years of operation at a large Military Treatment Facility. MATERIALS AND METHODS: In 2014 the Physical Medicine and Rehabilitation and Physical Therapy (PT) services designed a novel acute spine clinic intended to directly receive ADSM with acute spine symptoms for an initial evaluation by a Physical Therapist. The inclusion criteria into the ASPC were: ADSM, pain less than or equal to 7 days, no more than three prior episodes of acute spine pain in the past 3 years, and not currently receiving care from Chiropractic, Pain Management, or PT services. The exclusion criteria were: significant and/or progressive neurological deficits, bowel or bladder dysfunction, unstable vital signs or fever, hematuria or extensive trauma. RESULTS: A total of 1,215 patients presented to the ASPC for evaluation between 2014 and 2019. The most common chief complaint was acute pain in the lumbar spine (73%), followed by cervical spine pain (15%), and thoracic spine pain (12%) represented the fewest. The average number of PT visits per patient was 3.5 (range 1-13) with 61.1% utilizing three or fewer visits. Over 95% of cases returned to work the same day as their initial evaluation. Sixty-six percent returned to work without restriction the same day as their initial evaluation. Light duty recommendations were provided to 412 (33.9%) patients ranging from one to 30 days, with greater than 85% of the light duty being less than 14 days. Recommendations to not return to work (sick-in-quarters) were issued to 56 (4.6%) patients. The sick-in-quarters recommendations were for a 24-hour period in 48 cases, 48 hours for seven cases, and 72 hours for one case. All encounters in which the patient first sought care at the ASPC for low back pain met the Healthcare Effectiveness Data Set standard for low back pain care of having no imaging within 28 days of the first encounter for nonspecific low back pain. A medical record review of 100 randomly selected patients within 12 months of the initial evaluation demonstrated decreased utilization of medication, imaging, and referral to surgical services. CONCLUSIONS: This innovative approach demonstrates the potential benefits of rapid access to treatment and education for patients with acute spine pain by a Physical Therapist. Modeling this approach at Military Treatment Facilities may lead to decreased utilization of medications, radiology services, specialty care referrals, and reduced cost of care provided to individuals with acute spine pain.