Psoas muscle area is an independent survival prognosticator in patients undergoing surgery for long-bone metastases

BACKGROUND

Predictive analytics is gaining popularity as an aid to treatment planning for patients with bone metastases, whose expected survival should be considered. Decreased psoas muscle area (PMA), a morphometric indicator of suboptimal nutritional status, has been associated with mortality in various cancers, but never been integrated into current survival prediction algorithms (SPA) for patients with skeletal metastases. This study investigates whether decreased PMA predicts worse survival in patients with extremity metastases and whether incorporating PMA into three modern SPAs (PATHFx, SORG-NG, and SORG-MLA) improves their performance.

METHODS

One hundred eighty-five patients surgically treated for long-bone metastases between 2014 and 2019 were divided into three PMA tertiles (small, medium, and large) based on their psoas size on CT. Kaplan-Meier, multivariable regression, and Cox proportional hazards analyses were employed to compare survival between tertiles and examine factors associated with mortality. Logistic regression analysis was used to assess whether incorporating adjusted PMA values enhanced the three SPAs' discriminatory abilities. The clinical utility of incorporating PMA into these SPAs was evaluated by decision curve analysis (DCA).

RESULTS

Patients with small PMA had worse 90-day and 1-year survival after surgery (log-rank test p < 0.001). Patients in the large PMA group had a higher chance of surviving 90 days (odds ratio, OR, 3.72, p = 0.02) and 1 year than those in the small PMA group (OR 3.28, p = 0.004). All three SPAs had increased AUC after incorporation of adjusted PMA. DCA indicated increased net benefits at threshold probabilities >0.5 after the addition of adjusted PMA to these SPAs.

CONCLUSIONS

Decreased PMA on CT is associated with worse survival in surgically treated patients with extremity metastases, even after controlling for three contemporary SPAs. Physicians should consider the additional prognostic value of PMA on survival in patients undergoing consideration for operative management due to extremity metastases.

Comparison of eight modern preoperative scoring systems for survival prediction in patients with extremity metastasis

BACKGROUND

Survival is an important factor to consider when clinicians make treatment decisions for patients with skeletal metastasis. Several preoperative scoring systems (PSSs) have been developed to aid in survival prediction. Although we previously validated the Skeletal Oncology Research Group Machine-learning Algorithm (SORG-MLA) in Taiwanese patients of Han Chinese descent, the performance of other existing PSSs remains largely unknown outside their respective development cohorts. We aim to determine which PSS performs best in this unique population and provide a direct comparison between these models.

METHODS

We retrospectively included 356 patients undergoing surgical treatment for extremity metastasis at a tertiary center in Taiwan to validate and compare eight PSSs. Discrimination (c-index), decision curve (DCA), calibration (ratio of observed:expected survivors), and overall performance (Brier score) analyses were conducted to evaluate these models' performance in our cohort.

RESULTS

The discriminatory ability of all PSSs declined in our Taiwanese cohort compared with their Western validations. SORG-MLA is the only PSS that still demonstrated excellent discrimination (c-indexes>0.8) in our patients. SORG-MLA also brought the most net benefit across a wide range of risk probabilities on DCA with its 3-month and 12-month survival predictions.

CONCLUSIONS

Clinicians should consider potential ethnogeographic variations of a PSS's performance when applying it onto their specific patient populations. Further international validation studies are needed to ensure that existing PSSs are generalizable and can be integrated into the shared treatment decision-making process. As cancer treatment keeps advancing, researchers developing a new prediction model or refining an existing one could potentially improve their algorithm's performance by using data gathered from more recent patients that are reflective of the current state of cancer care.

High prevalence of Wilms tumor 1 expression in multiple myeloma and plasmacytoma: A cohort of 142 Asian patients' samples

Wilms tumor 1 (WT1) is a promising target antigen for cancer immunotherapy. However, WT1 protein expression and its clinical correlation in multiple myeloma (MM) patients are still limited. We, therefore, investigated WT1 expression in 142 bone marrow and plasmacytoma samples of MM patients at different stages of the disease by immunohistochemistry. The correlations between WT1 expression and clinical parameters or treatment outcomes were evaluated. The overall positive rate of WT1 expression was 91.5%; this high prevalence was found in both bone marrow and plasmacytoma samples, regardless of the disease status. Cytoplasmic WT1 expression was correlated with high serum free light chain ratio at presentation. However, no significant association between WT1 expression and treatment outcome was observed. This study confirms the high prevalence of WT1 expression in an Asian cohort of MM, encouraging the development of immunotherapy targeting WT1 in MM patients, particularly in those with extramedullary plasmacytoma or relapsed disease.

Factors affecting prognosis in hepatocellular carcinoma patients post-transarterial chemoembolization

BACKGROUND

To evaluate the factors influencing the achievement of a sustained complete response (CR) and overall survival (OS) in hepatocellular carcinoma (HCC) patients undergoing transarterial chemoembolization (TACE).

METHODS

We retrospectively reviewed the records of HCC patients who underwent TACE as the first modality of treatment between 2014 and 2019. We investigated the factors affecting sustained CR (no recurrence within 6 months) and OS (time from diagnosis until either death or last follow-up).

RESULTS

The study enrolled 161 patients; 159 (98.8%) had cirrhosis. Post-TACE, 19.9% (32/161) achieved sustained CR. In the multivariate analysis, a tumor size &lt; 5 cm was a positive factor for achieving sustained CR (odds ratio, 5.012; p = 0.006). In the proportional hazards model, the factors associated with decreased survival included alcohol-related liver disease (hazards ratio [HR] 1.683; p = 0.036), presence of symptoms (HR 1.816; p = 0.005) and portal hypertension (HR 1.608; p = 0.038) at initial diagnosis, serum alpha-fetoprotein (AFP) &gt; 100 ng/mL (HR 2.082; p &lt; 0.001), and higher Child-Pugh classification (HR 1.1.639; p = 0.024). Achievement of sustained CR (HR, 0.355; p = 0.002) was independently associated with increased survival.

CONCLUSIONS

The tumor size was a predictive factor for sustained CR. Alcohol-related liver disease, presence of symptoms and portal hypertension at initial diagnosis, elevated serum AFP, liver reserve status, and achieved sustained CR were independent factors affecting survival. We demonstrated the effect of alcohol-related liver disease on survival after TACE. Our results will aid physicians in the management and prognostication of HCC.

A machine learning algorithm for predicting prolonged postoperative opioid prescription after lumbar disc herniation surgery. An external validation study using 1,316 patients from a Taiwanese cohort

BACKGROUND CONTEXT

Preoperative prediction of prolonged postoperative opioid prescription helps identify patients for increased surveillance after surgery. The SORG machine learning model has been developed and successfully tested using 5,413 patients from the United States (US) to predict the risk of prolonged opioid prescription after surgery for lumbar disc herniation. However, external validation is an often-overlooked element in the process of incorporating prediction models in current clinical practice. This cannot be stressed enough in prediction models where medicolegal and cultural differences may play a major role.

PURPOSE

The authors aimed to investigate the generalizability of the US citizens prediction model SORG to a Taiwanese patient cohort.

STUDY DESIGN

Retrospective study at a large academic medical center in Taiwan.

PATIENT SAMPLE

Of 1,316 patients who were 20 years or older undergoing initial operative management for lumbar disc herniation between 2010 and 2018.

OUTCOME MEASURES

The primary outcome of interest was prolonged opioid prescription defined as continuing opioid prescription to at least 90 to 180 days after the first surgery for lumbar disc herniation at our institution.

METHODS

Baseline characteristics were compared between the external validation cohort and the original developmental cohorts. Discrimination (area under the receiver operating characteristic curve and the area under the precision-recall curve), calibration, overall performance (Brier score), and decision curve analysis were used to assess the performance of the SORG ML algorithm in the validation cohort. This study had no funding source or conflict of interests.

RESULTS

Overall, 1,316 patients were identified with sustained postoperative opioid prescription in 41 (3.1%) patients. The validation cohort differed from the development cohort on several variables including 93% of Taiwanese patients receiving NSAIDS preoperatively compared with 22% of US citizens patients, while 30% of Taiwanese patients received opioids versus 25% in the US. Despite these differences, the SORG prediction model retained good discrimination (area under the receiver operating characteristic curve of 0.76 and the area under the precision-recall curve of 0.33) and good overall performance (Brier score of 0.028 compared with null model Brier score of 0.030) while somewhat overestimating the chance of prolonged opioid use (calibration slope of 1.07 and calibration intercept of -0.87). Decision-curve analysis showed the SORG model was suitable for clinical use.

CONCLUSIONS

Despite differences at baseline and a very strict opioid policy, the SORG algorithm for prolonged opioid use after surgery for lumbar disc herniation has good discriminative abilities and good overall performance in a Han Chinese patient group in Taiwan. This freely available digital application can be used to identify high-risk patients and tailor prevention policies for these patients that may mitigate the long-term adverse consequence of opioid dependence: https://sorg-apps.shinyapps.io/lumbardiscopioid/.

Genomic and Transcriptomic Analyses Reveals ZNF124 as a Critical Regulator in Highly Aggressive Medulloblastomas

Medulloblastoma (MB) is the most common malignant pediatric brain tumor, however, the mechanisms underlying tumorigenesis in different MB subgroups remain incompletely understood. Although previous studies of MB predisposition have been conducted in tertiary referral centers primarily in Caucasian cohorts, it is not unclear clear whether there exist population-specific genetic alterations in MBs. In this study, we investigated the contribution of genomic and transcriptomic alterations to the risk of malignant MB in the Chinese population (designated as the Asian cohort). We analyze the genomic and transcriptomic alterations of the Asian MB cohort by using a combination of whole-exome sequencing (WES) and RNA-deep-sequencing. In addition, we integrate publicly available data with the Asian MB cohort and identify a subset of potential MB-driving genes specifically enriched in each of the MB subgroups. We further characterize a newly identified group-3-enriched transcriptional regulator, ZNF124, and demonstrate that ZNF124 is critical for the growth of the most aggressive group-3 MB cells. Together, our analyses indicate conserved yet distinct genetic alterations and gene expression patterns of MBs between different ethnic groups. Our studies further provide an important resource for identifying potential tumor-driving factors in MBs, enhancing our understanding of the disease process for developing ethnically targeted therapies in patients with MB.

Ethnicity Does Not Influence Glycemic Outcomes or Diabetes Remission After Sleeve Gastrectomy or Gastric Bypass in a Multiethnic Asian Cohort

BACKGROUND

In Asia, metabolic-bariatric surgery (MBS) rates have grown rapidly in parallel with rising prevalence of obesity and type 2 diabetes (T2D).

OBJECTIVE

The objective of this study was to identify factors that influence glycemic outcomes and diabetes remission 12 months after sleeve gastrectomy (SG) or gastric bypass (GB) in a multiethnic Asian cohort.

SETTING

The study's setting was in a tertiary hospital in Singapore.

METHODS

Data from 145 T2D patients who had SG (37%) or GB (63%) and at least 1-year follow-up were analyzed. Diabetes remission was defined as hemoglobin A1c ≤ 6.0% without diabetes medications. Analysis involved binary logistic regression to identify predictors and general linear regression for variables associated with glycemic improvement after surgery.

RESULTS

Baseline parameters are as follows: BMI 40.0 ± 7.6 kg/m², A1c 8.4 ± 1.6%, diabetes duration 9.3 years, ethnic composition: Chinese (51.7%), Malay (23.4%), Indian (20.7%), Others (4.1%). 55.9% achieved diabetes remission at 1 year. Baseline A1c, baseline BMI, and diabetes duration were significant pre-operative factors for remission (cumulative R ² = 0.334). At 12 months, percentage weight loss was similar after SG (24.1 ± 7.4%) and GB (25.4 ± 7.4%, p = 0.31). Greater A1c decrease was seen with GB compared to SG (2.7 ± 1.6 vs 2.0 ± 1.5%, p = 0.006), significant even after adjustment for weight loss, age, BMI, baseline A1c, and diabetes duration (p = 0.033). Weight loss at 12 months also correlated independently with A1c reduction. Ethnicity did not influence weight loss, diabetes remission, or glycemic control after MBS.

CONCLUSION

Baseline A1c, baseline BMI, and diabetes duration independently predict diabetes remission after MBS. GB is more effective in controlling T2D compared to SG despite similar weight loss, whereas ethnicity does not play a significant role in the multiethnic Asian cohort.

Longitudinal Analysis Between Maternal Feeding Practices and Body Mass Index (BMI): A Study in Asian Singaporean Preschoolers

Bidirectional studies between maternal feeding practices with subsequent child weight are limited, with no studies in Asian populations. In longitudinal analyses, we assessed the directionality of the associations between maternal feeding practices and body mass index (BMI) in preschoolers. Participants were 428 mother child dyads from the GUSTO (Growing Up in Singapore Toward healthy Outcomes) cohort. Feeding practices were assessed using the Comprehensive Feeding Practices Questionnaire (CFPQ) at age 5 y. Child BMI was measured at ages 4 and 6 y. BMI and maternal feeding practices subscales were transformed to SD scores and both directions of their associations examined with multivariable linear regression and pathway modeling. Higher BMI at age 4 was associated with lower encouragement of balance and variety (β = −0.33; 95%CI: −0.53, −0.13), lower pressure to eat (β = −0.49; −0.68, −0.29) and higher restriction (β = 1.10; 0.67, 1.52) at age 5, adjusting for confounders and baseline feeding practices at 3 years. In the reverse direction, only pressure and restriction at age 5 were associated with lower and higher child BMI at age 6 years, respectively. After the adjustment for baseline BMI at age 5, the association with pressure was attenuated to non-significance (β = 0.01 (−0.01, 0.03), while the association with restriction remained significant (β = 0.02; 0.002, 0.03). Overall, associations from child BMI to maternal restriction for weight control and pressure feeding practices was stronger than the association from these maternal feeding practices to child BMI (Wald's statistics = 24.3 and 19.5, respectively; p < 0.001). The strength and directionality suggests that the mothers in the Asian population were likely to adopt these feeding practices in response to their child's BMI, rather than the converse.

Clinical Trial Registry Number and Website 

This study was registered at clinicaltrials.gov as NCT01174875 (www.clinicaltrials.gov, NCT01174875).

Social Demography of Transitional Dietary Patterns in Thailand: Prospective Evidence from the Thai Cohort Study

In recent decades, a health-risk transition with changes in diet and lifestyle in low and middle-income countries (LMICs) led to an emergence of chronic diseases. These trends in Southeast Asian LMICs are not well studied. Here, we report on transitional dietary patterns and their socio-demographic predictors in Thai adults. Dietary data in 2015 were from a random sub-sample (N = 1075) of 42,785 Thai Cohort Study (TCS) members who completed all three TCS surveys (2005, 2009, 2013). Principle Component Analysis identified dietary patterns and multivariable linear regression assessed associations (Beta estimates (ß) and confidence intervals (CIs)) between socio-demographic factors and dietary intake pattern scores. Four dietary patterns emerged: Healthy Transitional, Fatty Western, Highly Processed, and Traditional. In women, higher income (≥30,001 Baht/month vs. ≤10,000) and managerial work (vs. office assistant) was associated with lower scores for Traditional (ß = −0.67, 95% CI −1.15, −0.19) and Fatty Western diets (ß = −0.60, 95% CI −1.14, −0.05), respectively. University education associated with lower Highly Processed (ß = −0.57, 95% CI −0.98, −0.17) and higher Traditional diet scores (ß = 0.42, 95% CI 0.03, 0.81). In men and women, urban residence associated with higher Fatty Western and lower Traditional diets. Local policy makers should promote healthy diets, particularly in urban residents, in men, and in low-SEP adults.

Body mass index and type 2 diabetes in Thai adults: defining risk thresholds and population impacts

Background

Body mass index (BMI) cut-off values (>25 and >30) that predict diabetes risk have been well validated in Caucasian populations but less so in Asian populations. We aimed to determine the BMI threshold associated with increased type 2 diabetes (T2DM) risk and to calculate the proportion of T2DM cases attributable to overweight and obesity in the Thai population.

Methods

Participants were those from the Thai Cohort Study who were diabetes-free in 2005 and were followed-up in 2009 and 2013 (n = 39,021). We used multivariable logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the BMI-T2DM association. We modelled non-linear associations using restricted cubic splines. We estimated population attributable fractions (PAF) and the number of T2DM incident cases attributed to overweight and obesity. We also calculated the impact of reducing the prevalence of overweight and obesity on T2DM incidence in the Thai population.

Results

Non-linear modelling indicated that the points of inflection where the BMI-T2DM association became statistically significant compared to a reference of 20.00 kg/m² were 21.60 (OR = 1.27, 95% CI 1.00–1.61) and 20.03 (OR = 1.02, 95% CI 1.02–1.03) for men and women, respectively. Approximately two-thirds of T2DM cases in Thai adults could be attributed to overweight and obesity. Annually, if prevalent obesity was 5% lower, ~13,000 cases of T2DM might be prevented in the Thai population.

Conclusions

A BMI cut-point of 22 kg/m², one point lower than the current 23 kg/m², would be justified for defining T2DM risk in Thai adults. Lowering obesity prevalence would greatly reduce T2DM incidence.

Electronic supplementary material

The online version of this article (10.1186/s12889-017-4708-7) contains supplementary material, which is available to authorized users.