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OBJECTIVE It is not clear whether there is an additive effect of social factors in keeping patients with cervical spondylotic myelopathy (CSM) from achieving both a minimum clinically important difference (MCID) in outcomes and satisfaction after surgery. The aim of this study was to explore the effect of multiple social factors on postoperative outcomes and satisfaction. METHODS This was a multiinstitutional, retrospective study of the prospective Quality Outcomes Database (QOD) CSM cohort, which included patients aged 18 years or older who were diagnosed with primary CSM and underwent operative management. Social factors included race (White vs non-White), education (high school or below vs above), employment (employed vs not), and insurance (private vs nonprivate). Patients were considered to have improved from surgery if the following criteria were met: 1) they reported a score of 1 or 2 on the North American Spine Society index, and 2) they met the MCID in patient-reported outcomes (i.e., visual analog scale [VAS] neck and arm pain, Neck Disability Index [NDI], and EuroQol-5D [EQ-5D]). RESULTS Of the 1141 patients included in the study, 205 (18.0%) had 0, 347 (30.4%) had 1, 334 (29.3%) had 2, and 255 (22.3%) had 3 social factors. The 24-month follow-up rate was > 80% for all patient-reported outcomes. After adjusting for all relevant covariates (p < 0.02), patients with 1 or more social factors were less likely to improve from surgery in all measured outcomes including VAS neck pain (OR 0.90, 95% CI 0.83–0.99) and arm pain (OR 0.88, 95% CI 0.80–0.96); NDI (OR 0.90, 95% CI 0.83–0.98); and EQ-5D (OR 0.90, 95% CI 0.83–0.97) (all p < 0.05) compared to those without any social factors. Patients with 2 social factors (outcomes: neck pain OR 0.86, arm pain OR 0.81, NDI OR 0.84, EQ-5D OR 0.81; all p < 0.05) or 3 social factors (outcomes: neck pain OR 0.84, arm pain OR 0.84, NDI OR 0.84, EQ-5D OR 0.84; all p < 0.05) were more likely to fare worse in all outcomes compared to those with only 1 social factor. CONCLUSIONS Compared to those without any social factors, patients who had at least 1 social factor were less likely to achieve MCID and feel satisfied after surgery. The effect of social factors is additive in that patients with a higher number of factors are less likely to improve compared to those with only 1 social factor.

PURPOSE Multidisciplinary molecular tumor boards (MTBs) decode complex genomic data into clinical recommendations. Although MTBs are well-established in the oncology practice in developed countries, this strategy needs to be better explored in developing countries. Herein, we describe the possible benefits and limitations of the first MTB established in Colombia. METHODS Demographic, clinical, and genomic information was collected between August 2020 and November 2021. By mid-2020, an MTB strategy was created to discuss clinical cases with one or more genomic alterations identified by next-generation sequencing using an open-access virtual platform. We characterized the patient population as benefiting from the recommended treatment option. We assessed the benefits and access to available targeted therapies that have the potential to change clinical management by making recommendations to treating oncologists on the basis of genomic profiling. However, we did not assess the treatment oncologists' compliance with MTB recommendations because they were not intended to replace clinical judgment/standard of care. RESULTS A total of 146 patients were included in the discussions of the MTB. The median age was 59 years, and 59.6% were women. Genomic results prompting a change in therapeutic decisions were obtained in 53.1% of patients (95% CI, 44.9 to 61.3). The most prevalent malignancy was non–small-cell lung cancer (51%). Other malignancies represented 60%, 50%, and 30% of patients with soft-tissue sarcomas, brain tumors, and breast cancer, respectively. CONCLUSION Using an open-access virtual platform, MTBs were feasible in low- and middle-income countries on the basis of the capability to provide the benefits and access to available targeted therapies that are not standard of care. Furthermore, MTB recommendations were made available to the treating oncologist in different locations across Colombia, providing the option to modify clinical management in most of these patients.

Abstract Recent advances in the field of immuno‐oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high‐throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi‐marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

AbstractBackgroundDiagnosing gastroesophageal reflux disease (GERD) can be challenging given varying symptom presentations, and complex multifactorial pathophysiology. The gold standard for GERD diagnosis is esophageal acid exposure time (AET) measured by pH‐metry. A variety of additional diagnostic tools are available. The goal of this consensus was to assess the individual merits of GERD diagnostic tools based on current evidence, and provide consensus recommendations following discussion and voting by experts.MethodsThis consensus was developed by 15 experts from nine countries, based on a systematic search of the literature, using GRADE (grading of recommendations, assessment, development and evaluation) methodology to assess the quality and strength of the evidence, and provide recommendations regarding the diagnostic utility of different GERD diagnosis tools, using AET as the reference standard.Key ResultsA proton pump inhibitor (PPI) trial is appropriate for patients with heartburn and no alarm symptoms, but nor for patients with regurgitation, chest pain, or extraesophageal presentations. Severe erosive esophagitis and abnormal reflux monitoring off PPI are clearly indicative of GERD. Esophagram, esophageal biopsies, laryngoscopy, and pharyngeal pH monitoring are not recommended to diagnose GERD. Patients with PPI‐refractory symptoms and normal endoscopy require reflux monitoring by pH or pH‐impedance to confirm or exclude GERD, and identify treatment failure mechanisms. GERD confounders need to be considered in some patients, pH‐impedance can identify supragrastric belching, impedance‐manometry can diagnose rumination.ConclusionsErosive esophagitis on endoscopy and abnormal pH or pH‐impedance monitoring are the most appropriate methods to establish a diagnosis of GERD. Other tools may add useful complementary information.

AbstractPurposeTo study the feasibility of using the Integral Quality Monitoring (IQM) system for routine quality assurance (QA) of photon beams.MethodsThe IQM system is a commercially available dose delivery verification tool, which consists of a spatially sensitive large area transmission ion chamber, mounted on the Linac collimator, and a calculation algorithm to predict the signals in response to radiation beams. By comparing the measured and predicted signals the system verifies the accuracy of beam delivery. The ion chamber unit is a battery powered system including a dual‐electrometer, temperature and pressure sensors, and inclinometers. The feasibility of using the IQM system for routine QA tests was investigated by measuring constancy values of beam parameters, with specially designed tests fields, and comparing them with those determined by a conventional system.ResultsThe sensitivity of the beam output constancy measurements by the IQM system was found to agree with those measured by a Farmer type ion chamber placed in water phantoms to within 0.1% for typical daily output variation of ± 0.5% and ± 1%. The beam symmetry was measured with a 4 cm × 4 cm aperture at multiple off‐axis distances and was found to have a highly linear relationship with those measured in a water phantom scan for intentionally introduced asymmetry between ‐3% and +3%. The beam flatness was measured with a two‐field ratio method and was found to be linearly correlated with those measured by water phantom scan. The dosimetric equivalent of a picket fence test performed by the IQM system can serve as a constancy check of the multileaf collimator (MLC) bank positioning test.ConclusionsThe IQM system has been investigated for constancy measurements of various beam parameters for photon beams. The results suggest that the system can be used for most of the routine QA tests effectively and efficiently.

Abstract The Infectious Diseases Society of America Training Program Directors Committee met in October 2022 and discussed an observed increase in clinical volume and acuity on infectious diseases (ID) services, and its impact on fellow education. Committee members sought to develop specific goals and strategies related to improving training program culture, preserving quality education on inpatient consult services and in the clinic, and negotiating change at the annual IDWeek Training Program Director meeting. This paper outlines a presentation of ideas brought forth at the meeting and is meant to serve as a reference document for infectious diseases training program directors seeking guidance in this area.

Adaptive therapy, an ecologically inspired approach to cancer treatment, aims to overcome resistance and reduce toxicity by leveraging competitive interactions between drug-sensitive and drug-resistant subclones, prioritizing patient survival and quality of life instead of killing the maximum number of cancer cells. In preparation for a clinical trial, we used endocrine-resistant MCF7 breast cancer to stimulate second-line therapy and tested adaptive therapy using capecitabine, gemcitabine, or their combination in a mouse xenograft model. Dose modulation adaptive therapy with capecitabine alone increased survival time relative to MTD but not statistically significantly (HR = 0.22, 95% CI = 0.043–1.1, p = 0.065). However, when we alternated the drugs in both dose modulation (HR = 0.11, 95% CI = 0.024–0.55, p = 0.007) and intermittent adaptive therapies, the survival time was significantly increased compared to high-dose combination therapy (HR = 0.07, 95% CI = 0.013–0.42, p = 0.003). Overall, the survival time increased with reduced dose for both single drugs (p < 0.01) and combined drugs (p < 0.001), resulting in tumors with fewer proliferation cells (p = 0.0026) and more apoptotic cells (p = 0.045) compared to high-dose therapy. Adaptive therapy favors slower-growing tumors and shows promise in two-drug alternating regimens instead of being combined.

OBJECTIVE The aim of this study was to identify predictors of the best 24-month improvements in patients undergoing surgery for cervical spondylotic myelopathy (CSM). For this purpose, the authors leveraged a large prospective cohort of surgically treated patients with CSM to identify factors predicting the best outcomes for disability, quality of life, and functional status following surgery. METHODS This was a retrospective analysis of prospectively collected data. The Quality Outcomes Database (QOD) CSM dataset (1141 patients) at 14 top enrolling sites was used. Baseline and surgical characteristics were compared for those reporting the top and bottom 20th percentile 24-month Neck Disability Index (NDI), EuroQol-5D (EQ-5D), and modified Japanese Orthopaedic Association (mJOA) change scores. A multivariable logistic model was constructed and included candidate variables reaching p ≤ 0.20 on univariate analyses. Least important variables were removed in a stepwise manner to determine the significant predictors of the best outcomes (top 20th percentile) for 24-month NDI, EQ-5D, and mJOA change. RESULTS A total of 948 (83.1%) patients with 24-month follow-up were included in this study. For NDI, 204 (17.9%) had the best NDI outcome and 200 (17.5%) had the worst NDI outcome. Factors predicting the best NDI outcomes included symptom duration less than 12 months (OR 1.5, 95% CI 1.1–1.9; p = 0.01); procedure other than posterior fusion (OR 1.5, 95% CI 1.03–2.1; p = 0.03); higher preoperative visual analog scale neck pain score (OR 1.2, 95% CI 1.1–1.3; p < 0.001); and higher baseline NDI (OR 1.06, 95% CI 1.05–1.07; p < 0.001). For EQ-5D, 163 (14.3%) had the best EQ-5D outcome and 169 (14.8%) had the worst EQ-5D outcome. Factors predicting the best EQ-5D outcomes included arm pain–only complaints (compared to neck pain) (OR 1.9, 95% CI 1.3–2.9; p = 0.002) and lower baseline EQ-5D (OR 167.7 per unit lower, 95% CI 85.0–339.4; p < 0.001). For mJOA, 222 (19.5%) had the best mJOA outcome and 238 (20.9%) had the worst mJOA outcome. Factors predicting the best mJOA outcomes included lower BMI (OR 1.03 per unit lower, 95% CI 1.004–1.05; p = 0.02; cutoff value of ≤ 29.5 kg/m 2 ); arm pain–only complaints (compared to neck pain) (OR 1.7, 95% CI 1.1–2.5; p = 0.02); and lower baseline mJOA (OR 1.6 per unit lower, 95% CI 1.5–1.7; p < 0.001). CONCLUSIONS Compared to the worst outcomes for EQ-5D, the best outcomes were associated with patients with arm pain–only complaints. For mJOA, lower BMI and arm pain–only complaints portended the best outcomes. For NDI, those with the best outcomes had shorter symptom durations, higher preoperative neck pain scores, and less often underwent posterior spinal fusions. Given the positive impact of shorter symptom duration on outcomes, these data suggest that early surgery may be beneficial for patients with CSM.

Background Remarkable interest is rising around middle meningeal artery embolization (MMAE) as an emerging alternative therapy for chronic subdural hematoma (cSDH). The study aims to highlight a large center experience and the variables associated with treatment failure and build experimental machine learning (ML) models for outcome prediction. Material and Methods A 2-year experience in MMAE for managing patients with chronic subdural hematoma was analyzed. Descriptive statistical analysis was conducted using imaging and clinical features of the patients and cSDH, which were subsequently used to build predictive models for the procedure outcome. The modeling evaluation metrics were the area under the ROC curve and F1-score. Results A total of 100 cSDH of 76 patients who underwent MMAE were included with an average follow-up of 6 months. The intervention had a per procedure success rate of 92%. Thrombocytopenia had a highly significant association with treatment failure. Two patients suffered a complication related to the procedure. The best performing machine learning models in predicting MMAE failure achieved an ROC-AUC of 70%, and an F1-score of 67%, including all patients with or without surgical intervention prior to embolization, and an ROC-AUC of 82% and an F1-score of 69% when only patients who underwent upfront MMAE were included. Conclusion MMAE is a safe and minimally invasive procedure with great potential in transforming the management of cSDH and reducing the risk of surgical complications in selected patients. An ML approach with larger sample size might help better predict outcomes and highlight important predictors following MMAE in patients with cSDH.