Predictive modeling of long-term opioid and benzodiazepine use after intradural tumor resection

Long-term postoperative outcomes of spinal cellular schwannoma: study of 93 consecutive cases

BACKGROUND CONTEXT

Cellular schwannoma (CS) is a rare tumor that accounts for 2.8%-5.2% of all benign schwannomas. There is a dearth of up-to-date information on spinal CS in the literature.

PURPOSE

The aims of this study were to identify the proportion of CS cases amongst spinal benign schwannoma, describe the clinical features of spinal CS, and identify prognostic factors for local recurrence by analyzing data from 93 consecutive CS cases.

STUDY DESIGN

Retrospective review.

PATIENT SAMPLE

We analyzed 93 PSGCT screened from 1,706 patients with spine CS who were treated at our institute between 2008 and 2021.

OUTCOME MEASURES

Demographic, radiographic, operative and postoperative data were recorded and analyzed.

METHODS

We compared the clinical features of spinal CS from the cervical, thoracic, lumbar and sacral segments. Prognostic factors for local recurrence-free survival (RFS) were identified by the Kaplan-Meier method. Factors with p≤.05 in univariate analysis were subjected to multivariate analysis by Cox regression analysis.

RESULTS

The proportion of spinal CS in all benign schwannomas was 6.7%. The mean and median follow-up times for the 93 patients in this study were 92.2 and 91.0 months respectively (range 36-182 months). Local recurrence was detected in 11 cases, giving an overall recurrence rate of 11.7%, with one patient death. Statistical analysis revealed that tumor size ≥5 cm, intralesional resection, and Ki-67 ≥5% were independent negative prognostic factors for RFS in spinal CS.

CONCLUSIONS

Whenever possible, en bloc resection is recommended for spinal CS. Long-term follow-up should be carried out for patients with tumor size ≥5 cm and postoperative pathological Ki-67 ≥5%.

Substance Use Disorders Are Independently Associated with Hospital Readmission Among Patients with Brain Tumors

BACKGROUND

Research on the effects of substance use disorders (SUDs) on postoperative outcomes within neurosurgical oncology has been limited. Therefore, the present study sought to quantify the effect of having a SUD on hospital length of stay, postoperative complication incidence, discharge disposition, hospital charges, 90-day readmission rates, and 90-day mortality rates following brain tumor surgery.

METHODS

The present study used data from patients who received surgical resection for brain tumor at a single institution between January 1, 2017, and December 31, 2019. The Mann-Whitney U test was used for bivariate analysis of continuous variables and Fisher exact test was used for bivariate analysis of categorical variables. Multivariate analysis was conducted using logistic regression models.

RESULTS

Our study cohort included a total of 2519 patients, 124 (4.9%) of whom had at least 1 SUD. More specifically, 90 (3.6%) patients had an alcohol use disorder, 27 (1.1%) had a cannabis use disorder, and 12 (0.5%) had an opioid use disorder. On bivariate analysis, 90-day hospital readmission was the only postoperative outcome significantly associated with a SUD (odds ratio 2.21, P = 0.0011). When controlling for patient age, sex, race, marital status, insurance, brain tumor diagnosis, 5-factor modified frailty index score, American Society of Anesthesiologists score, and surgery number, SUDs remained significantly and independently associated with 90-day readmission (odds ratio 1.82, P = 0.013).

CONCLUSIONS

In patients with brain tumor, SUDs significantly and independently predict 90-day hospital readmission after surgery. Targeted management of patients with SUDs before and after surgery can optimize patient outcomes and improve the provision of high-value neurosurgical care.

Health Care Resource Utilization in Management of Opioid-Naive Patients With Newly Diagnosed Neck Pain

IMPORTANCE

Research has uncovered heterogeneity and inefficiencies in the management of idiopathic low back pain, but few studies have examined longitudinal care patterns following newly diagnosed neck pain.

OBJECTIVE

To understand health care utilization in patients with new-onset idiopathic neck pain.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used nationally sourced longitudinal data from the IBM Watson Health MarketScan claims database (2007-2016). Participants included adult patients with newly diagnosed neck pain, no recent opioid use, and at least 1 year of continuous postdiagnosis follow-up. Exclusion criteria included prior or concomitant diagnosis of traumatic cervical disc dislocation, vertebral fractures, myelopathy, and/or cancer. Only patients with at least 1 year of prediagnosis lookback were included. Data analysis was performed from January 2021 to January 2022.

MAIN OUTCOMES AND MEASURES

The primary outcome of interest was 1-year postdiagnosis health care expenditures, including costs, opioid use, and health care service utilization. Early services were those received within 30 days of diagnosis. Multivariable regression models and regression-adjusted statistics were used.

RESULTS

In total, 679 030 patients (310 665 men [45.6%]) met the inclusion criteria, of whom 7858 (1.2%) underwent surgery within 1 year of diagnosis. The mean (SD) age was 44.62 (14.87) years among nonsurgical patients and 49.69 (9.53) years among surgical patients. Adjusting for demographics and comorbidities, 1-year regression-adjusted health care costs were $24 267.55 per surgical patient and $515.69 per nonsurgical patient. Across all health care services, $95 379 949 was accounted for by nonsurgical patients undergoing early imaging who did not receive any additional conservative therapy or epidural steroid injections, for a mean (SD) of $477.53 ($1375.60) per patient and median (IQR) of $120.60 ($20.70-$452.37) per patient. On average, patients not undergoing surgery, physical therapy, chiropractic manipulative therapy, or epidural steroid injection, who underwent either early advanced imaging (magnetic resonance imaging or computed tomography) or both early advanced and radiographic imaging, accumulated significantly elevated health care costs ($850.69 and $1181.67, respectively). Early conservative therapy was independently associated with 24.8% (95% CI, 23.5%-26.2%) lower health care costs.

CONCLUSIONS AND RELEVANCE

In this cross-sectional study, early imaging without subsequent intervention was associated with significantly increased health care spending among patients with newly diagnosed idiopathic neck pain. Early conservative therapy was associated with lower costs, even with increased frequency of therapeutic services, and may have reduced long-term care inefficiency.

Prediction of Discharge Status and Readmissions after Resection of Intradural Spinal Tumors

Objective

Intradural spinal tumors are uncommon and while associations between clinical characteristics and surgical outcomes have been explored, there remains a paucity of literature unifying diverse predictors into an integrated risk model. To predict postresection outcomes for patients with spinal tumors.

Methods

IBM MarketScan Claims Database was queried for adult patients receiving surgery for intradural tumors between 2007 and 2016. Primary outcomes-of-interest were nonhome discharge and 90-day postdischarge readmissions. Secondary outcomes included hospitalization duration and postoperative complications. Risk modeling was developed using a regularized logistic regression framework (LASSO, least absolute shrinkage and selection operator) and validated in a withheld subset.

Results

A total of 5,060 adult patients were included. Most surgeries utilized a posterior approach (n=5,023, 99.3%) and tumors were most commonly found in the thoracic region (n=1,941, 38.4%), followed by the lumbar (n=1,781, 35.2%) and cervical (n=1,294, 25.6%) regions. Compared to models using only tumor-specific or patient-specific features, our integrated models demonstrated better discrimination (area under the curve [AUC] [nonhome discharge] = 0.786; AUC [90-day readmissions] = 0.693) and accuracy (Brier score [nonhome discharge] = 0.155; Brier score [90-day readmissions] = 0.093). Compared to those predicted to be lowest risk, patients predicted to be highest-risk for nonhome discharge required continued care 16.3 times more frequently (64.5% vs. 3.9%). Similarly, patients predicted to be at highest risk for postdischarge readmissions were readmitted 7.3 times as often as those predicted to be at lowest risk (32.6% vs. 4.4%).

Conclusion

Using a diverse set of clinical characteristics spanning tumor-, patient-, and hospitalization-derived data, we developed and validated risk models integrating diverse clinical data for predicting nonhome discharge and postdischarge readmissions.

Clinical Prediction Modeling in Intramedullary Spinal Tumor Surgery

Artificial intelligence is poised to influence various aspects of patient care, and neurosurgery is one of the most uprising fields where machine learning is being applied to provide surgeons with greater insight about the pathophysiology and prognosis of neurological conditions. This chapter provides a guide for clinicians on relevant aspects of machine learning and reviews selected application of these methods in intramedullary spinal cord tumors. The potential areas of application of machine learning extend far beyond the analyses of clinical data to include several areas of artificial intelligence, such as genomics and computer vision. Integration of various sources of data and application of advanced analytical approaches could improve risk assessment for intramedullary tumors.