Probability Of Response Research Articles

Identity Disclosure and Anthropomorphism in Voice Chatbot Design: A Field Experiment

Fueled by the widespread adoption of algorithms and artificial intelligence, the use of chatbots has become increasingly popular in various business contexts. In this paper, we study how to effectively and appropriately use voice chatbots, particularly by leveraging the two design features identity disclosure and anthropomorphism, and evaluate their impact on the firm operational performance. In collaboration with a large truck-sharing platform, we conducted a field experiment that randomly assigned 11,000 truck drivers to receive outbound calls from the voice chatbot dispatcher of our focal platform. Our empirical results suggest that disclosing the identity of the chatbot at the beginning of the conversation negatively affects operational performance, leading to around 11% reduction in the response probability. However, humanizing the voice chatbot by adding our proposed anthropomorphism features (i.e., interjections and filler words) significantly improves response probability, conversation length, and the probability of order acceptance intention by over 5.6%, 24.9%, and 10.1%, respectively. Moreover, even when the chatbot’s identity is disclosed along with humanizing features, the operational outcomes still improve. This finding suggests that enhancing anthropomorphism may potentially counteract the negative effects of chatbot identity disclosure. Finally, we propose one plausible explanation for the performance improvement—the enhanced trust between humans and algorithms—and provide empirical evidence that drivers are more likely to disclose information to chatbot dispatchers with anthropomorphism features. Our proposed anthropomorphism improvement solutions are currently being implemented and utilized by our collaborator platform. This paper has been This paper was accepted by Felipe Caro for the Special Issue on the Human-Algorithm Connection. Funding: This study is supported by the National Natural Science Foundation of China [Grants 72172169 and 91646125], Program for Innovation Research at the Central University of Finance and Economic, and Shanghai Pujiang Program. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.03833 .

Complete pathologic response in esophageal adenocarcinoma: does it make a difference?

Advancements in neoadjuvant regimens for esophageal adenocarcinoma have enabled some patients to achieve complete pathologic response at time of esophagectomy. There are currently limited data detailing this trend or the implications of complete pathologic response on survival. The National Cancer Database was used to identify 16,169 patients with esophageal adenocarcinoma that received trimodal therapy including esophagectomy between 2006 and 2020. Of these, 11.4% had complete pathologic response at esophagectomy. Patient factors, staging characteristics, and survival trends were evaluated. In patients diagnosed between 2016 and 2020, the rate of complete pathologic response was 17.5%. Female sex (OR 1.295, 95% CI 1.134-1.481, p = 0.0001), Black race (OR 1.729, 95% CI 1.362-2.196, p = 0.0002), Hispanic ethnicity (OR 1.418, 95% CI 1.073-1.875, p = 0.0141), and later era of diagnosis (2016-2020 OR 2.898, 95% CI 2.508-3.349, p < 0.0001) were independent predictors of complete pathologic response. Clinical stage II disease was associated with an increased probability of complete pathologic response (OR 1.492, 95% CI 1.19-1.871) while clinical stage III disease had a decreased probability of complete pathologic response (OR 0.762, 95% CI 0.621-0.936, p < 0.0001). Complete pathologic response conveyed a strong survival benefit, with a median survival of 86.4months (95% CI 73.9-102.1) versus 30.7months (95% CI 29.8-31.7, p < 0.0001) in those without complete pathologic response. Four-year median survival was also higher in those with complete pathologic response (63.3%, 95% CI 60.8-66.0% vs. 39.2%, 95% CI 38.4-40.1%, p < 0.0001). In summary, complete pathologic response is associated with a profound survival advantage in patients with esophageal adenocarcinoma. Such knowledge carries implications for patient counseling, prognostication, and surveillance and demonstrates a need for improved identification of complete clinical response prior to esophagectomy.

Impact of twice-daily budesonide foam administration on early clinical response and endoscopic remission in patients with ulcerative colitis: a post hoc analysis.

Early treatment response of ulcerative colitis (UC) symptom resolution is desirable. This post hoc analysis evaluated efficacy outcomes, including endoscopic remission, by responder status and the influence of once-daily (QD) versus twice-daily (BID) budesonide foam dosing in patients with UC. Data were pooled from phase 2 and phase 3 clinical trials of budesonide rectal foam QD or BID or placebo for up to 12weeks. Outcomes were evaluated by treatment and budesonide administration regimen and by responder group: early (rectal bleeding subscore [RBS] 0 from Week 2 through Week 6), delayed (RBS 0 at Week 6), and nonresponder (RBS>0 at Week 6). The main analysis set included 55 (QD) and 120 (BID) budesonide-treated patients and 116 placebo-treated patients. At Week 6, the trend in early response rate was significant among treatment groups (BID, 45.3%; QD, 32.1%; placebo, 12.8%; P<0.0001). Among BID recipients, trends for complete endoscopic remission rate (Mayo endoscopic score [MES]=0) and endoscopic remission rate (MES=0 or 1) were significant among responder status groups (early responder, 67.4% and 95.4%, respectively; delayed responder, 48.1% and 85.2%; nonresponder, 24.0% and 64.0%; P<0.001 for both). Regardless of the administration regimen, most early responders achieved endoscopic remission at Week 6. Among responder status groups, early responders' cumulative non-relapse period was greatest (P=0.07). A BID budesonide administration regimen is preferred to increase the probability of early response and, following endoscopic remission, a better prognosis after stopping treatment.

Real-world Clinical Effectiveness and Safety of Vedolizumab and Adalimumab in Biologic-naive Patients With Crohn's Disease: Results From the EVOLVE Study.

This study evaluated the real-world effectiveness and safety of vedolizumab versus adalimumab over 12 months of treatment in biologic-naive patients with Crohn's disease (CD), using data from the EVOLVE study. A comparison of vedolizumab and adalimumab may help to better position them in the therapeutic algorithm for moderate-to-severe CD. Data were collected from medical records of patients with CD aged ≥18 years initiating treatment with adalimumab or vedolizumab between May 2014 and July 2017. Adjusted analyses were performed using inverse probability weighting to account for differences in baseline characteristics. Cumulative rates for clinical effectiveness outcomes and treatment persistence were estimated using Kaplan-Meier analyses. Disease-related exacerbations, serious adverse events (SAEs), and serious infections (SIs) were also assessed. Data from 218 vedolizumab- and 144 adalimumab-treated patients were analyzed. Adjusted cumulative rates of clinical remission were greater with vedolizumab than with adalimumab (66.3% vs. 46.4%; P=0.006). Probability of treatment persistence was higher with vedolizumab (89.3% vs. 77.5%; P=0.024); probabilities of clinical response (68.5% vs. 61.1%; P=0.586) and mucosal healing (67.7% vs. 56.0%; P=0.562) were similar. SAEs were less likely to occur with vedolizumab [hazard ratio, 0.45 (95% confidence interval, 0.22-0.93)]; however, the likelihood of SIs [0.27 (0.06-1.20)], CD exacerbations [0.91 (0.56-1.47)], and CD-related surgeries [1.55 (0.21-11.15)] was comparable between the 2 groups. In a real-world setting, biologic-naive patients with CD treated with vedolizumab demonstrated a greater likelihood of drug persistence and achieving clinical remission, with equivalent rates of response and mucosal healing versus adalimumab-treated patients.

Assessing aortic flow with doppler echocardiography in cardiogenic shock: A crucial diagnostic tool.

Cardiogenic shock still has a high mortality. In order to correctly manage these patients, it is useful to have available haemodynamic parameters, invasive and non-invasive. The aim of this review is to show the current evidence on the use of echocardiographic aortic flow assessment by left ventricular outflow tract - velocity time integral. Publications relevant to the discussion of echocardiographic aortic flow assessment by left ventricular outflow tract - velocity time integral and cardiogenic shock, were retrieved from PubMed®. Left ventricular outflow tract - velocity time integral is an easily sampled and reproducible parameter that has already been shown to have prognostic value in various cardiovascular pathologies, including myocardial infarction and heart failure. Although there are still few data available in the literature, the LVOT-VTI also seems to have an important role in CS from prognosis to guidance in the escalation/de-escalation of vasoactive therapy and to support devices by allowing an estimate of patient's probability of response to fluid administration. Aortic flow assessment can become a very useful invasive parameter in the management of cardiogenic shock.

Prediction model for treatment response of primary membranous nephropathy with nephrotic syndrome.

To investigate the predictors and establish a nomogram model for the prediction of the response to treatment in primary membranous nephropathy (PMN) with nephrotic syndrome (NS). The clinical, laboratory, pathological and follow-up data ofpatients withbiopsy-proven membranous nephropathy at the Affiliated Hospital of QingdaoUniversity were collected. A total of 373 patients were randomly assigned into development group (n = 262) and validation group (n = 111). Logistic regression analysis was performed in the development group to determine the predictors of treatment response. A nomogram model was established based on the multivariate logistic regression analysis and validated in the validation group. The C-index and calibration plots were used for the evaluation of the discrimination and calibration performance, respectively. Serum albumin levels (OR = 1.151, 95% CI 1.078-1.229, P < 0.001) and glomerular C3 deposition (OR = 0.407, 95% CI 0.213-0.775, P = 0.004) were identified as independent predictive factors for treatment response in PMN with NS, then a nomogram was established combining the above indicators and treatment regimen. The C-indices of this model were 0.718 (95% CI 0.654-0.782) and 0.789 (95% CI 0.705-0.873) in the development and validation groups, respectively. The calibration plots showed that the predicted probabilities of the model were consistent with the actual probabilities (P > 0.05), which indicated favorable performance of this model in predicting the treatment response probability. Serum albumin levels and glomerular C3 deposition were predictors for treatment response of PMN with NS. A novel nomogram model with good discrimination and calibration was constructed to predict treatment response probability at an early stage.

Assessment of pharmacokinetics-pharmacodynamics to support omadacycline dosing regimens for the treatment of patients with acute bacterial skin and skin structure infections.

Pharmacokinetic-pharmacodynamic (PK-PD) relationships for efficacy were evaluated using data from omadacycline-treated patients with acute bacterial skin and skin structure infections (ABSSSI) enrolled in two phase 3 studies. Patients received omadacycline 100 mg intravenously (IV) every 12 hours for two doses, followed by 100 mg IV every 24 hours (q24h), with the option to switch to 300 mg oral (PO) q24h after 3 days or 450 mg PO q24h for two doses, followed by 300 mg PO q24h for a total duration of 7-14 days. Clinical response was evaluated at 48-72 hours [early clinical response (ECR)], end of treatment (EOT), and 7-14 days after EOT. Using a population pharmacokinetic (PK) model and PK data from patients with Staphylococcus aureus at baseline, omadacycline free-drug plasma area under the concentration-time curve (AUC) values were determined, and the relationships between free-drug plasma AUC:MIC ratio and dichotomous efficacy endpoints were evaluated. Using these relationships, the population PK model, simulation, and an omadacycline MIC distribution for S. aureus, mean percent probabilities of response were evaluated. Statistically significant PK--PD relationships were identified for ECR (P = 0.016 and 0.013 for optimized two- and three-group free-drug plasma AUC:MIC ratios, respectively). At an MIC value of 0.5 µg/mL, percent probabilities of model-predicted success for ECR based on the univariable PK-PD relationships using continuous and two-group free-drug plasma AUC:MIC ratio variables were 91.9 and 95.6%, respectively, for the IV-to-PO dosing regimen and 89.3 and 88.4%, respectively, for the PO-only dosing regimen. These data support for omadacycline IV-to-PO and PO-only dosing regimens for ABSSSI and an omadacycline susceptibility breakpoint of 0.5 µg/mL for S. aureus.

An Improved Wiener Path Integral Approach for Stochastic Response Estimation of Nonlinear Systems Under Non-White Excitation

Abstract An improved Wiener path integral (WPI) approach is developed for predicting the stochastic response probability density functions (PDFs) of nonlinear systems under non-white excitation. Specifically, the excitation process is modeled as the output of a filter whose input is Gaussian white noise, the joint response PDF of the nonlinear system is expressed as a functional integral of the stochastic action over the space of all possible trajectories between the initial and final states, and the second-order variation of the stochastic action is recast to a quadratic form and taken into account in the estimation of the joint response PDF. Compared to the standard WPI approach where the second-order variation of the stochastic action is regarded as a constant, the improved WPI approach developed herein considers the fluctuations of the second-order variation of the stochastic action in the computational domain, thus improving the accuracy of the stochastic response estimation. Two numerical examples are illustrated, and the nonstationary response PDFs estimated by the improved WPI approach agree well with the Monte Carlo simulation results.

Dysregulation of kappa opioid receptor neuromodulation of lateral habenula synaptic function following a repetitive mild traumatic brain injury

Mild traumatic brain injury (mTBI) increases the risk of affective disorders, anxiety and substance use disorder. The lateral habenula (LHb) plays an important role in pathophysiology of psychiatric disorders. Recently, we demonstrated a causal link between mTBI-induced LHb hyperactivity due to excitation/inhibition (E/I) imbalance and motivational deficits in male mice using a repetitive closed head injury mTBI model. A major neuromodulatory system that is responsive to traumatic brain injuries, influences affective states and also modulates LHb activity is the dynorphin/kappa opioid receptor (Dyn/KOR) system. However, the effects of mTBI on KOR neuromodulation of LHb function are unknown. Here, we first used retrograde tracing in male and female Cre mouse lines and identified several major KOR-expressing and two prominent Dyn-expressing inputs projecting to the mouse LHb, highlighting the medial prefrontal cortex (mPFC) and the ventromedial nucleus of the hypothalamus (VMH) as the main LHb-projecting Dyn inputs that regulate KOR signaling to the LHb. We then functionally evaluated the effects of in vitro KOR modulation of spontaneous synaptic activity within the LHb of male and female sham and mTBI mice at 4 week post-injury. We observed sex-specific differences in spontaneous release of glutamate and GABA from presynaptic terminals onto LHb neurons with higher levels of presynaptic glutamate and GABA release in females compared to male mice. However, KOR effects on the spontaneous E/I ratios and synaptic drive ratio within the LHb did not differ between male and female sham and mTBI mice. KOR activation generally suppressed spontaneous glutamatergic transmission without altering GABAergic transmission, resulting in a significant but sex-similar reduction in net spontaneous E/I and synaptic drive ratios in LHb neurons of sham mice. Following mTBI, while responses to KOR activation at LHb glutamatergic synapses remained intact, LHb GABAergic synapses acquired an additional sensitivity to KOR-mediated inhibition where we observed a reduction in GABA release probability in response to KOR stimulation in LHb neurons of mTBI mice. Further analysis of percent change in spontaneous synaptic ratios induced by KOR activation revealed that independent of sex mTBI switches KOR-driven synaptic inhibition of LHb neurons (normally observed in sham mice) in a subset of mTBI mice toward synaptic excitation resulting in mTBI-induced divergence of KOR actions within the LHb. Overall, we uncovered the sources of major Dyn/KOR-expressing synaptic inputs projecting to the mouse LHb. We demonstrate that an engagement of intra-LHb Dyn/KOR signaling provides a global KOR-driven synaptic inhibition within the mouse LHb independent of sex. The additional engagement of KOR-mediated action on LHb GABAergic transmission by mTBI could contribute to the E/I imbalance after mTBI, with Dyn/KOR signaling serving as a disinhibitory mechanism for LHb neurons of a subset of mTBI mice.

Impact of ALDH1A1 and NQO1 gene polymorphisms on the response and toxicity of chemotherapy in Bangladeshi breast cancer patients.

Cyclophosphamide, Epirubicin/Doxorubicin, 5-fluorouracil (CEF or CAF) chemotherapy has long been a standard first-line treatment for breast cancer. The genetic variations of enzymes that are responsible for the metabolism of these drugs have been linked to altered treatment response and toxicity. Two drug-metabolizing enzymes ALDH1A1 and NQO1 are critically involved in the pathways of CEF/CAF metabolism. This study aimed to evaluate the effect of ALDH1A1 (rs13959) and NQO1 (rs1800566) polymorphisms on treatment response and toxicities caused by adjuvant (ACT) and neoadjuvant chemotherapy (NACT) where CEF/CAF combination was used to treat Bangladeshi breast cancer patients. A total of 330 patients were recruited from various hospitals, with 150 receiving neoadjuvant chemotherapy and 180 receiving adjuvant chemotherapy. To extract genomic DNA, a non-enzymatic simple salting out approach was adopted. The polymerase chain reaction-restriction fragment length polymorphism method was used to detect genetic polymorphisms. Unconditional logistic regression was used to derive odds ratios (ORs) with 95% confidence intervals (CIs) to study the association between genetic polymorphisms and clinical outcome and toxicity. A statistically significant association was observed between ALDH1A1 (rs13959) polymorphism and treatment response (TT vs. CC: aOR = 6.40, p = 0.007; recessive model: aOR = 6.38, p = 0.002; allele model: p = 0.032). Patients with the genotypes TT and CT + TT of the NQO1 (rs1800566) polymorphism had a significantly higher risk of toxicities such as anemia (aOR = 0.34, p = 0.006 and aOR = 0.58, p = 0.021), neutropenia (aOR = 0.42, p = 0.044 and aOR = 0.57, p = 0.027), leukopenia (aOR = 0.33, p = 0.010 and aOR = 0.46, p = 0.005), and gastrointestinal toxicity (aOR = 0.30, p = 0.02 and aOR = 0.38, p = 0.006) when compared to the wild CC genotype, while patients with the genotype CT had a significant association with gastrointestinal toxicity (aOR = 0.42, p = 0.02) and leukopenia (aOR = 0.52, p = 0.010). The TT and CT + TT genotypes of rs13959 had a significantly higher risk of anemia (aOR = 2.00, p = 0.037 and aOR = 1.68, p = 0.029). There was no significant association between rs1800566 polymorphism and treatment response. Polymorphisms in ALDH1A1 (rs13959) and NQO1 (rs1800566) may be useful in predicting the probability of treatment response and adverse effects from CEF or CAF-based chemotherapy in breast cancer patients.

Revisiting which language declines more in Spanish-English bilinguals with Alzheimer's disease: Longitudinal decline patterns on the multilingual naming test

Theories of bilingual language production predict that bilinguals with Alzheimer's disease (AD) should exhibit one of two decline patterns. Either parallel decline of both languages (if decline reflects damage to semantic representations that are accessed by both languages), or asymmetrical decline, with greater decline of the nondominant language (if decline reflects reduced ability to resolve competition from the dominant language with disease progression). Only two previous studies examined decline longitudinally with one showing parallel, and the other asymmetrical, decline. We examined decline over 2–7 years (3.9 on average) in Spanish-English bilinguals (N = 23). Logistic regression revealed a parallel decline pattern at one year from baseline, but an asymmetrical decline pattern over the longer decline period, with greater decline of the nondominant language (when calculating predicted probabilities of a correct response). The asymmetrical decline pattern was significantly greater for the nondominant language only when including item-difficulty in the model. Exploratory analyses across dominance groups looking at proportional decline relative to initial naming accuracy further suggested that decline of the nondominant language may be more precipitous if that language was acquired later in life, but the critical interaction needed to support this possibility was not statistically significant in a logistic regression analysis. These results suggest that accessibility of the nondominant language may initially be more resilient in early versus more advanced AD, and that AD affects shared semantic representations before executive control declines to a point where the ability to name pictures in single-language testing block is disrupted. Additional work is needed to determine if asymmetrical decline patterns are magnified by late age of acquisition of the nondominant language, and if more subtle impairments to executive control underlie impairments to language switching that occur in the earliest stages of AD (even preclinically).

Random Vibration Analysis of Double Deck Rocking Self-Centering Pier Under Seismic Excitation

This paper investigates nonlinear random vibration of double deck rocking self-centering pier structure subjected to seismic excitation. First of all, a novel type of double deck rocking self-centering pier that offers better resilience is designed. The stochastic dynamical model of the system is then established, in which the seismic excitation is viewed as Kanai–Tajimi filtered white noise and the self-centering restoring force is characterized by classical flag-shaped hysteretic model. Subsequently, the self-centering restoring force is decomposed into equivalent quasi-linear elastic and damping forces by adopting the harmonic balance (HB) scheme. Following this, the stochastic averaging (SA) technique is implemented to derive the averaged Itô equation. The steady-state response probability density with respect to the amplitudes is solved from the averaged Fokker–Planck–Kolmogorov (FPK) equation. Finally, the effects of system parameters on the stochastic response of the double deck rocking self-centering pier structure are performed, and validated by the Monte Carlo simulation (MCS). In addition, with the help of the Laplace transform, the transition function as well as conditional power spectral density are achieved, which are combined with the steady-state probability density to obtain the power spectral density response. This research will contribute to the optimal seismic design of double-deck rocking self-centering piers.

Multi-output multi-physics-informed neural network for learning dimension-reduced probability density evolution equation with unknown spatio-temporal-dependent coefficients

The Dimension-Reduced Probability Density Evolution Equation (DR-PDEE) offers a promising approach for evaluating probability density evolution in stochastic dynamical systems. Physics-Informed Neural Networks (PINNs) are well-suited for solving DR-PDEE due to their ability to encode physical laws into the learning process. However, challenges arise from the spatio-temporal-dependence of unknown intrinsic drift and diffusion coefficients, which drive DR-PDEE, along with their derivatives. To address these challenges, a novel framework called Multi-Output Multi-Physics-Informed Neural Network (MO-MPINN) is proposed to predict the evolution of time-varying coefficients and response probability density simultaneously. MO-MPINN features multiple output neurons, eliminating the necessity for distinct identification of unknown spatio-temporal-dependent coefficients separately. It uses parallel subnetworks to reduce training complexity and embeds multiple physical laws in the loss function to ensure an accurate representation of the underlying principles. Leveraging automatic differentiation, MO-MPINN efficiently computes derivatives of coefficients without resorting to numerical differentiation. The framework is applicable to high-dimensional stochastic nonlinear systems with double randomness in structural parameters and excitations. Several structures are presented to validate the performance of the MO-MPINN. This study introduces a new paradigm for solving partial differential equations involving differentiation of spatio-temporal-dependent coefficients.

Outcomes Analysis of Yttrium-90 Radioembolization for Tumors Other Than Metastatic Colorectal Cancer from the Radiation-Emitting SIR-Spheres in Nonresectable (RESiN) Registry

PurposeTo characterize the response and survival outcomes of yttrium-90 (90Y) transarterial radioembolization (TARE) for unresectable, liver-dominant metastases from primary neoplasms other than colorectal carcinoma. Materials and MethodsThis study included 1,474 patients enrolled in the Radiation-Emitting Society of Interventional Radiology (SIR)–Spheres in Nonresectable Liver Tumor registry who received resin 90Y-TARE as part of their oncologic management for unresectable primary or secondary liver tumors (NCT 02685631). Of these patients, 33% (481/1,474) were treated for liver metastases of noncolorectal origin (m-non-CRC) compared with 34% (497/1,474) treated for metastatic colorectal cancer (mCRC) and 34% (496/1,474) treated for hepatocellular carcinoma. Treatment response and cancer survival probabilities were computed and compared for each primary cancer type. The Kaplan-Meier method and log-rank test were used to compare survival outcomes. ResultsRadiological responses were observed in 12 unique cancer types, mostly heavily pretreated malignancies refractory to multiple lines of systemic therapies. The overall use of resin 90Y-TARE in m-non-CRC resulted in better treatment outcomes in terms of duration of response, progression-free survival, time to progression, and overall survival (P = .04, P = .02, P = .01, and P = .04, respectively). Analyses of cancer cell types revealed that metastatic neuroendocrine tumor, sarcoma, and ovarian, renal, prostate, and breast cancers were associated with superior treatment outcomes, whereas worse treatment outcomes were observed in metastatic lung, gastric, pancreatic, and esophageal cancers. ConclusionsReal-world data demonstrate the use of resin 90Y-TARE in m-non-CRC refractory to standard chemotherapy. For some cell types, this expanded use achieved superior treatment outcomes relative to the reference standard of mCRC, suggesting the need for inquiry into broadened indications for 90Y-TARE.

Baseline tumor-infiltrating lymphocyte patterns and response to immune checkpoint inhibition in metastatic cutaneous melanoma

IntroductionThe presence of tumor-infiltrating lymphocytes (TILs) in melanoma has been linked to survival. Their predictive capability for immune checkpoint inhibition (ICI) response remains uncertain. Therefore, we investigated the association between treatment response and TILs in the largest cohort to date and analyzed if this association was independent of known clinical predictors. MethodsIn this multicenter cohort study, patients who received first-line anti-PD1 ± anti-CTLA4 for advanced melanoma were identified. TILs were scored on hematoxylin and eosin (H&E) slides of primary melanoma and pre-treatment metastases using the validated TILs-WG, Clark and MIA score. The primary outcome was objective response rate (ORR), with progression free survival and overall survival being secondary outcomes. Univariable and multivariable logistic regression and Cox proportional hazard were performed, adjusting for known clinical predictors. ResultsMetastatic melanoma specimens were available for 650 patients and primary specimens for 565 patients. No association was found in primary melanoma specimens. In metastatic specimens, a 10-point increase in the TILs-WG score was associated with a higher probability of response (aOR 1.17, 95 % CI 1.07–1.28), increased PFS (HR 0.93, 95 % CI 0.87–0.996), and OS (HR 0.94, 95 % CI 0.89–0.99). When categorized, patients in the highest tertile TILs-WG score (15–100 %) compared to the lowest tertile (0 %) had a longer median PFS (13.1 vs. 7.3 months, p = 0.04) and OS (49.4 vs. 19.5 months, p = 0.003). Similar results were noted using the MIA and Clark scores. ConclusionIn advanced melanoma patients, TIL patterns on H&E slides of pre-treatment metastases, regardless of measurement method, are independently associated with ICI response. TILs are easily scored on readily available H&Es, facilitating the use of this biomarker in clinical practice.

Safety and efficacy of flumatinib as later-line therapy in patients with chronic myeloid leukemia.

To evaluate the efficacy and safety of flumatinib in the later-line treatment of Chinese patients with Philadelphia chromosome-positive chronic-phase chronic myeloid leukemia (CP-CML previously treated with tyrosine kinase inhibitors (TKIs). Patients with CML-CP were evaluated for the probabilities of responses including complete hematologic response (CHR), cytogenetic response, and molecular response (MR) and adverse events (AEs) after the later-line flumatinib therapy. Of 336 enrolled patients with median age 50 years, median duration of treatment with flumatinib was 11.04 (2-25.23) months. Patients who achieved clinical responses at baseline showed maintenance of CHR, complete cytogenetic response (CCyR)/2-log molecular response (MR2), major molecular response (MMR), and 4-log molecular response or deep molecular response (MR4/DMR) in 100%, 98.9%, 98.6%, and 92.9% patients, respectively. CHR, CCyR/MR2, MMR, and MR4/DMR responses were achieved in 86.4%, 52.7%, 49.6%, and 23.5% patients respectively, which showed the lack of respective clinical responses at baseline. The patients without response at baseline, treated with flumatinib as 2L TKI, having no resistance to prior TKI or only resistance to imatinib, with response to last TKI, and with BCR::ABL ≤10% had higher CCyR/MR2, MMR, or MR4/DMR. The AEs observed during the later-line flumatinib treatment were tolerable and consistent with those reported with the first-line therapy. Flumatinib was effective and safe in patients who are resistant or intolerant to other TKIs. In particular, 2L flumatinib treatment induced high response rates and was more beneficial to patients without previous 2G TKI resistance, thus serving as a probable treatment option for these patients.

Estimating response propensities in nonprobability surveys using machine learning weighted models

Propensity Score Adjustment (PSA) is a widely accepted method to reduce selection bias in nonprobability samples. In this approach, the (unknown) response probability of each individual is estimated in a nonprobability sample, using a reference probability sample. This, the researcher obtains a representation of the target population, reflecting the differences (for a set of auxiliary variables) between the population and the nonprobability sample, from which response probabilities can be estimated.Auxiliary probability samples are usually produced by surveys with complex sampling designs, meaning that the use of design weights is crucial to accurately calculate response probabilities. When a linear model is used for this task, maximising a pseudo log-likelihood function which involves design weights provides consistent estimates for the inverse probability weighting estimator. However, little is known about how design weights may benefit the estimates when techniques such as machine learning classifiers are used.This study aims to investigate the behaviour of Propensity Score Adjustment with machine learning classifiers, subject to the use of weights in the modelling step. A theoretical approximation to the problem is presented, together with a simulation study highlighting the properties of estimators using different types of weights in the propensity modelling step.

Study of aerodynamic damping of a crosswind-excited circular cylinder and its application to full-scale flexible structures

The accurate assessment of aerodynamic damping is essential when estimating the impact of aero-elastic effects on crosswind-excited line-like structures. This study aims to determine the crosswind aerodynamic damping of a circular cylinder by curve-fitting to the response probability density function. The generalized Van der Pol oscillator model is employed to depict the nonlinearity associated with amplitude-dependent aerodynamic damping. The initial section of this study presents the theoretical foundation of the identified approach used in this research. Subsequently, the efficacy of the identification methodology is validated by means of a stochastic simulation of the crosswind response of a circular cylinder. Moreover, identification of nonlinear aerodynamic damping is further accomplished by the utilization of an aero-elastic model wind tunnel test. The identified nonlinear aerodynamic damping is then utilized to determine the response statistical quantities for a total of 16 chimneys. The determined aerodynamic damping provides a satisfactory assessment of the peak response, which is crucial for design considerations.

Compare the efficacy of antifungal agents as primary therapy for invasive aspergillosis: a network meta-analysis

BackgroundSeveral antifungal agents are available for primary therapy in patients with invasive aspergillosis (IA). Although a few studies have compared the effectiveness of different antifungal agents in treating IA, there has yet to be a definitive agreement on the best choice. Herein, we perform a network meta-analysis comparing the efficacy of different antifungal agents in IA.MethodsWe searched PubMed, Embase, and the Cochrane Central Register of Controlled Clinical Trials databases to find studies (both randomized controlled trials [RCTs] and observational) that reported on treatment outcomes with antifungal agents for patients with IA. The study quality was assessed using the revised tool for risk of bias and the Newcastle Ottawa scale, respectively. We performed a network meta-analysis (NMA) to summarize the evidence on antifungal agents’ efficacy (favourable response and mortality).ResultsWe found 12 studies (2428 patients) investigating 11 antifungal agents in the primary therapy of IA. There were 5 RCTs and 7 observational studies. When treated with monotherapy, isavuconazole was associated with the best probability of favourable response (SUCRA, 77.9%; mean rank, 3.2) and the best reduction mortality against IA (SUCRA, 69.1%; mean rank, 4.1), followed by voriconazole and posaconazole. When treated with combination therapy, Liposomal amphotericin B plus caspofungin was the therapy associated with the best probability of favourable response (SUCRA, 84.1%; mean rank, 2.6) and the best reduction mortality (SUCRA, 88.2%; mean rank, 2.2) against IA.ConclusionThese findings suggest that isavuconazole, voriconazole, and posaconazole may be the best antifungal agents as the primary therapy for IA. Liposomal amphotericin B plus caspofungin could be an alternative option.

Efficient path integral approach via analytical asymptotic expansion for nonlinear systems under Gaussian white noise

In this paper an efficient formulation of the Path integral (PI) approach is developed for determining the response probability density functions (PDFs) and first-passage statistics of nonlinear oscillators subject to stationary and time-modulated external Gaussian white noise excitations. Specifically, the evolution of the response PDF is obtained in short time steps, by using a discrete version of the Chapman-Kolmogorov equation and assuming a Gaussian form for the conditional response PDF. Next, the technique involves proceeding to treating the problem via an analytical asymptotic expansion procedure, namely the Laplace’s method of integration. In this manner, the repetitive double integrals involved in the standard implementation of the PI approach are evaluated in a closed form, while the response and first-passage PDFs are obtained by mundane step-by-step application of the derived approximate analytical expression. It is shown that the herein proposed formulation can drastically decrease the associated computational cost by several orders of magnitude, as compared to both the standard PI technique and Monte Carlo solution (MCS) approach. A number of nonlinear oscillators are considered in the numerical examples. Notably, for these systems both response PDFs and first-passage probabilities are presented, whereas comparisons with pertinent MCS data demonstrate the efficiency and accuracy of the technique.