scholarly journals Impacts of remdesivir on dynamics and efficacy stratified by the severity of COVID- 19: a simulated two-arm controlled study

Author(s):  
Ting-Yu Lin ◽  
Wei-Jung Chang ◽  
Chen-Yang Hsu ◽  
Chao-Chih Lai ◽  
Amy Ming-Fang Yen ◽  
...  

Background: The impact of remdesivir on length of stay of hospitalization, high-risk state, and death stratified by the severity of COVID-19 at enrollment is controversial. Methods: We applied a simulated two-arm controlled study design to the data on compassionate use of remdesivir as a secondary analysis. Dynamics of risk states and death from COVID-19 patients defined by the six-point disease severity recommended by the WHO R&D and the time to discharge from hospital were used to evaluate the efficacy of remdesivir treatment compared with standard care. Results: Stratified by the risk state at enrollment, low-risk patients exhibited the highest efficacy of remdesivir in reducing subsequent progression to high-risk state by 67% (relative risk (RR)=0.33,95% CI: 0.30-0.35) and further to death by 55% (RR=0.45, 95%CI: 0.39-0.50). For the medium-risk patients, less but still statistically significant efficacy results were noted in reducing progression to high-risk state by 52% (RR=0.48, 95% CI: 0.45-0.51) and further to death by 40% (RR=0.60, 95% CI:0.54-0.66). High-risk state patients treated with remdesivir led to a 25% statistically significant reduction in death (RR=0.75, 95% CI: 0.69-0.82). Regarding the outcome of discharge, remdesivir treatment was most effective for medium-risk patients at enrollment (RR: 1.41, 95% CI: 1.35-1.47) followed by high- (RR=1.34, 95% CI: 1.27-1.42) and low-risk patients (RR=1.28, 95% CI: 1.25-1.31). Conclusion: Our results with a simulated two-arm controlled study have provided a new insight into the precision treatment of remdesivir for COVID-19 patients based on risk-stratified efficacy.

2021 ◽  
Vol 12 ◽  
Author(s):  
Mengdi Chen ◽  
Deyue Liu ◽  
Weilin Chen ◽  
Weiguo Chen ◽  
Kunwei Shen ◽  
...  

BackgroundThe 21-gene assay recurrence score (RS) provides additional information on recurrence risk of breast cancer patients and prediction of chemotherapy benefit. Previous studies that examined the contribution of the individual genes and gene modules of RS were conducted mostly in postmenopausal patients. We aimed to evaluate the gene modules of RS in patients of different ages.MethodsA total of 1,078 estrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative breast cancer patients diagnosed between January 2009 and March 2017 from Shanghai Jiao Tong University Breast Cancer Data Base were included. All patients were divided into three subgroups: Group A, ≤40 years and premenopausal (n = 97); Group B, >40 years and premenopausal (n = 284); Group C, postmenopausal (n = 697). The estrogen, proliferation, invasion, and HER2 module scores from RS were used to characterize the respective molecular features. Spearman correlation and analysis of the variance tests were conducted for RS and its constituent modules.ResultsIn patients >40 years, RS had a strong negative correlation with its estrogen module (ρ = −0.76 and −0.79 in Groups B and C) and a weak positive correlation with its invasion module (ρ = 0.29 and 0.25 in Groups B and C). The proliferation module mostly contributed to the variance in young patients (37.3%) while the ER module contributed most in old patients (54.1% and 53.4% in Groups B and C). In the genetic high-risk (RS >25) group, the proliferation module was the leading driver in all patients (ρ = 0.38, 0.53, and 0.52 in Groups A, B, and C) while the estrogen module had a weaker correlation with RS. The impact of ER module on RS was stronger in clinical low-risk patients while the effect of the proliferation module was stronger in clinical high-risk patients. The association between the RS and estrogen module was weaker among younger patients, especially in genetic low-risk patients.ConclusionsRS was primarily driven by the estrogen module regardless of age, but the proliferation module had a stronger impact on RS in younger patients. The impact of modules varied in patients with different genetic and clinical risks.


2021 ◽  
Author(s):  
Rossella Murtas ◽  
Nuccia Morici ◽  
Chiara Cogliati ◽  
Massimo Puoti ◽  
Barbara Omazzi ◽  
...  

BACKGROUND The coronavirus disease 2019 (COVID-19) pandemic has generated a huge strain on the health care system worldwide. The metropolitan area of Milan, Italy was one of the most hit area in the world. OBJECTIVE Robust risk prediction models are needed to stratify individual patient risk for public health purposes METHODS Two predictive algorithms were implemented in order to foresee the probability of being a COVID-19 patient and the risk of being hospitalized. The predictive model for COVID-19 positivity was developed in 61.956 symptomatic patients, whereas the model for COVID-19 hospitalization was developed in 36.834 COVID-19 positive patients. Exposures considered were age, gender, comorbidities and symptoms associated with COVID-19 (vomiting, cough, fever, diarrhoea, myalgia, asthenia, headache, anosmia, ageusia, and dyspnoea). RESULTS The predictive models showed a good fit for predicting COVID-19 disease [AUC 72.6% (95% CI 71.6%-73.5%)] and hospitalization [AUC 79.8% (95% CI 78.6%-81%)]. Using these results, 118,804 patients with COVID-19 from October 25 to December 11, 2020 were stratified into low, medium and high risk for COVID-19 severity. Among the overall population, 67.030 (56%) were classified as low-risk, 43.886 (37%) medium-risk, and 7.888 (7%) high-risk, with 89% of the overall population being assisted at home, 9% hospitalized, and 2% dead. Among those assisted at home, most people (60%) were classified as low risk, whereas only 4% were classified at high risk. According to ordinal logistic regression, the OR of being hospitalised or dead was 5.0 (95% CI 4.6-5.4) in high-risk patients and 2.7 (95% CI 2.6-2.9) in medium-risk patients, as compared to low-risk patients. CONCLUSIONS A simple monitoring system, based on primary care datasets with linkage to COVID-19 testing results, hospital admissions data and death records may assist in proper planning and allocation of patients and resources during the ongoing COVID-19 pandemic.


2020 ◽  
Vol 38 (4_suppl) ◽  
pp. 795-795
Author(s):  
Mehmet Akce ◽  
Katerina Mary Zakka ◽  
Mckenna Penely ◽  
Renjian Jiang ◽  
Olatunji B. Alese ◽  
...  

795 Background: Clinico-pathological high risk features are frequently utilized in adjuvant chemotherapy (AC) decisions in stage II colorectal cancer and their utility in stage II appendiceal adenocarcinoma (AA) is less established. The aim of this study is to determine the impact of high risk features on clinical outcomes and whether high risk features are predictive of AC benefit in stage II AA. Methods: Patients with pathological stage II AA between 2010 and 2015 were identified from the National Cancer Database (NCDB) using ICD-O-3 morphology and topography codes: 8140, 8480 and C18.1. High risk stage II AA was defined as having at least one of the following clinicopathological features: T4 tumor, < 12 lymph nodes examined, poorly differentiated histology, positive margins, or lymphovascular invasion. Patients with none of these features were defined as low-risk. Results: A total of 1,040 patients were identified. 51.0% males, 84.5% Caucasian; median age 61 (range, 19-90). 46.4% were determined to have high-risk stage II AA. High-risk status was associated with worse OS compared to low-risk in univariate (HR 1.55; 95% CI 1.18-2.02; p = 0.001) and multivariable analyses (HR 1.36; 95% CI 1.03-1.79; p = 0.028). High-risk stage II AA patients had significantly worse 5-year OS compared to low-risk patients (67.1% vs. 74.5%, p = 0.0013). AC was administered in 34.4% (n = 166) of high-risk patients and in 36.5% (n = 203) of low-risk patients. Among high-risk patients, AC was not associated with better OS in univariate (HR 0.86; 95% CI 0.59-1.26; p = 0.722) and multivariable analyses (HR 1.35; 95% CI 0.90-2.04; p = 0.324) compared to no AC. Similarly, among low-risk patients, AC was not associated with better OS in univariate (HR 0.92; 95% CI 0.60-1.39; p = 0.813) and multivariable analyses (HR 1.27; 95% CI 0.81-2.02; p = 0.334) compared to no AC. For high-risk patients, 5-year OS was 68.3% in patients that received AC vs. 66.5% in patients that did not (p = 0.722). For low-risk patients, 5-year OS was 74.0% in patients that received AC vs. 76.3% in patients that did not (p = 0.813). Conclusions: High-risk stage II AA patients had significantly worse 5-year OS compared to low-risk patients. AC did not improve survival regardless of high risk features in stage II AA.


2018 ◽  
Vol 36 (4_suppl) ◽  
pp. 845-845
Author(s):  
Ofer Margalit ◽  
Ronac Mamtani ◽  
Yu-Xiao Yang ◽  
Kim Anna Reiss ◽  
Talia Golan ◽  
...  

845 Background: The IDEA pooled analysis compared 3 to 6 months of adjuvant chemotherapy for newly defined low- and high-risk stage III colon cancer patients, suggesting low-risk patients may be offered only 3 months of treatment. We aimed to evaluate the benefit of monotherapy vs doublet chemotherapy in low and high IDEA risk groups. Methods: Using the NCDB (2004-2014) we identified 56,728 and 47,557 individuals as low and high IDEA risk groups, respectively. We used multivariate COX regression to evaluate the magnitude of survival differences between IDEA risk groups, according to treatment intensity (doublet vs monotherapy). In a secondary analysis, we examined the predictive value of subgroups of age. Results: Low and high IDEA risk groups derived similar benefit from doublet chemotherapy compared to monotherapy, with hazard ratios of 0.83 (95%CI 0.79-0.86) and 0.80 (95%CI 0.78-0.83), respectively. The only subpopulations that did not benefit from doublet chemotherapy were low-risk patients above the age of 72 (HR = 0.95, 95%CI 0.90-1.01) and high-risk patients above the age of 85 (HR = 0.90, 95%CI 0.77-1.05). Conclusions: IDEA risk classification does not predict benefit from doublet chemotherapy in stage III colon cancer. However, omission of oxaliplatin can be considered in IDEA low-risk patients above the age of 72.


2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 72-72
Author(s):  
John L. Gore ◽  
Darlene Dai ◽  
Robert Benjamin Den ◽  
Kasra Yousefi ◽  
Tiffany Le ◽  
...  

72 Background: Prostate cancer patients and providers confront uncertainty as they consider adjuvant or salvage radiation therapy (ART, SRT) after radical prostatectomy (RP). We prospectively evaluated the impact of the Decipher RP test, which predicts metastasis risk after RP, on decision-making for postoperative radiation therapy. Methods: Between October 2016 and May 2017, 1,319 patients treated with RP and considering ART or SRT were enrolled into a Medicare Certification and Training Registry (CTR). Providers submitted a management recommendation based on initial clinical and pathology findings prior to obtaining the Decipher RP test and again upon receiving test results. Only Medicare patients that met the Local Coverage Determination inclusion criteria (i.e., non-organ confined prostate cancer or positive margins or rising PSA) and whose provider was certified in the CTR registry were included in the analysis. Results: Based on clinical variables alone, treatment was recommended for 26% of adjuvant and 19% of salvage patients. Obtaining a Decipher score, changed treatment recommendations in 34% (95% CI 30-39%) and 28% (95% CI 19-38%) of men considering adjuvant or salvage therapy respectively. Among men considering ART, 9% of Decipher low risk patients and 45% of Decipher high-risk patients were recommended treatment. Multivariable logistic regression demonstrated that – independent of pathology risk factors, a high-risk Decipher score was associated with an odds ratio of 7.3 (95% CI 3.9-14.2 p < 0.001) in the adjuvant and 5.5 (95% CI, 1.3-27.8, p = 0.026) in the salvage setting. Conclusions: A prospective CTR demonstrated that use of Decipher resulted in significant changes in treatment decisions for Medicare beneficiaries with PCa considering adjuvant and salvage therapies. Ongoing prospective studies aim at determining how increased use of therapy in men with high Decipher risk impacts oncologic outcomes and whether decreased use in Decipher low risk individuals improves health related quality of life without harming patient survival.


2020 ◽  
Vol 38 (15_suppl) ◽  
pp. TPS2086-TPS2086
Author(s):  
Nathan Handley ◽  
Adam Binder ◽  
Michael Li ◽  
Aliya Rogers ◽  
Valerie Pracilio Csik

TPS2086 Background: Acute care utilization (ACU), encompassing both emergency department visits and hospitalizations, is common in patients with cancer, with nearly three quarters of patients with advanced disease hospitalized at least once in the year after their diagnosis. Efforts to prospectively identify these patients prior to ACU have led to the development of a variety of scoring systems for specific cancer patient populations, including the elderly and those initiating palliative infusional chemotherapy. Prospectively identifying patients may enable early interventions to reduce ACU. However, few studies have demonstrated effective implementation of such prediction tools in clinical practice. We developed an oncology risk score (ORS) for active oncology patients (defined as patients with an active cancer diagnosis in the last 12 months who had a Medical Oncology encounter in a 180-day period ) to prospectively determine risk of ACU. Patients are defined as high risk (18% of patients, accounting for 57% of historical ACU), intermediate risk (25% of patients, accounting for 25% of ACU), or low risk (56% of patients, accounting for 18% of ACU) by the ORS. We are currently deploying a pragmatic implementation initiative to evaluate the impact of targeted nurse navigator (NN) outreach to patients defined as high risk for ACU by the ORS. Methods: The ORS is embedded within the health system electronic medical record. The ORS will be queried on a weekly basis. NNs will contact identified patients, prioritizing patients not yet identified by the navigation team by other means. Following chart review, NNs will either meet patients in person (if a visit is already planned within 24 hours) or complete standard navigation outreach and documentation (consisting of phone call and barrier assessment, as well as appropriate nursing intervention) if no visit is planned. NNs will determine follow up cadence based on clinical judgement. Efficacy will be determined using a case-control method. Case patients will be OCM patients defined as high risk by the ORS (historical n = 289); control patients will be non-OCM high risk patients (historical n = 388). The total number of patients in the case and control groups, as well as the proportion of patients in the group utilizing acute care, will be monitored over time. Proportion of high risk patients known to navigation will be tracked. ACU in medium and low risk groups will also be monitored. Targeted outreach to high risk patients using the ORS began on 2/5/2019.


2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Bhanu Prasad ◽  
Maryam Jafari ◽  
Lexis Gordon ◽  
Navdeep Tangri ◽  
Joanne Kappel

Abstract Background and Aims: Multidisciplinary clinics (MDC’s) were established in Canada to offer a variety of support systems (diabetes care, social support, easy access to pharmacists, dietitians, specialty trained nurses), to monitor and delay progression through timed lab investigations and visits in conjunction with the Nephrologist. The reasons for better outcomes have been identified as better education, focus on self-care, dietary interventions, timely transplant referrals, modality education, lower hospitalizations and mortality. Treating all patients with chronic kidney disease (CKD) as part of a multidisciplinary care team runs the risk of adding unwarranted labs, interventions, polypharmacy and costs. Kidney Failure Risk Equation (KFRE) uses routine laboratory and clinical data, to stratify patients into three risk categories (low, medium, and high risk) of progression. KFRE has been shown to accurately estimate progression to kidney failure in adults with CKD. The objectives of the study were to i) validate the KFRE in our CKD patients, ii) evaluate health care utilization of patients based on the risk of progression in our province, Saskatchewan. iii) identify the subgroup of patients that benefit most from follow up in MDC. Methods: We conducted a retrospective study on 1007 patients with CKD stages G3 and G4 in two CKD multidisciplinary clinics in the province of Saskatchewan, Canada (January 2004-December 2012). The predicted risk of kidney failure (low, medium high) for each patient was calculated using the 8-variable KFRE. Patients were followed for five years to validate the KFRE; data on initiation of dialysis or death was collected. Cost of delivery of care per patient per year in the CKD clinic was determined. Health care utilization was evaluated by measuring the number/cost of hospital admissions, cardiovascular and thoracic (CVT) surgery, non-nephrology specialist appointments, and medications. Results: There were more patients in G 3 (n= 533) than in G 4 (n=474). 313 (59%), 150 (28%), and 70 (13%) were in low, medium and high-risk categories for G 3 CKD. 275 (58%), 86 (18%), and 113 (24%) were in similar categories for G 4. The mean age (SD) was 71 (12.8) years. The number of patients &gt; 65 years of age was 75%. 57% were men, mean GFR (mls/min/1.73m2) for G3 was 40 (7.8) and 23 (4) for G4. Of the G3 patients, 4% of low risk, 11% of the medium risk and 26% of the high risk progressed to dialysis by 5 years. In G 4 patients, 7% of low risk, 17% of medium risk and 48% of high risk progressed to dialysis over 2 years. These results validate the KFRE in our population. The cost of care per patient in MDC was $ 3800 (CAD) per year. There was a difference in the cost of medications, number and cost of (inpatient hospitalizations, cardiovascular surgeries, non-Nephrology specialist visits, and day surgeries) between low risk patients vs high risk patients in G4 patients. Conclusion: We performed a cost-effectiveness analysis of our MDC’s and show that very few patients at low-risk of progression advance to ESRD. They are also unlikely to benefit from intensive care management and better managed in primary care with advice from tertiary centres. Individual programs have significant opportunity to improve health care delivery by identifying the sub- groups that benefit the most from MDC based on the risk of progression to allow optimal utilization of resources. At $ 3800 (CAD) per patient, we suggest that MDC’s are best utilized by patients with medium and high risk of progression. Further, we show that patients that the low-risk patients were older, had fewer inpatient visits, had lesser drug costs, underwent fewer cardiovascular surgeries, had fewer day surgery visits, and fewer non-nephrology specialist visits. This is the first study to our knowledge that focuses on health care utilization based on the risk of disease progression rather than the stage of CKD.


2009 ◽  
Vol 29 (2_suppl) ◽  
pp. 153-157 ◽  
Author(s):  
Narayan Prasad ◽  
Amit Gupta ◽  
Archana Sinha ◽  
Anurag Singh ◽  
Raj Kumar Sharma ◽  
...  

Background Case-mix comorbidities and malnutrition influence outcome in continuous ambulatory peritoneal dialysis (CAPD) patients. In the present study, we analyzed the influence of stratified comorbidities on nutrition indices and survival in CAPD patients. Patients and Methods We categorized 373 CAPD patients (197 with and 176 without diabetes) into three risk groups: low—age under 70 years and no comorbid illness; medium—age 70 – 80 years, or any age with 1 comorbid illness, or age under 70 years with diabetes; high—age over 80 years, or any age with 2 comorbid illnesses. We then compared nutrition indices and malnutrition by subjective global assessment (SGA) between the three groups. Survival was compared using Kaplan–Meier survival analysis. Results Mean daily calorie and protein intakes in the low-risk group (21 ± 6.7 Kcal/kg, 0.85 ± 0.28 g/kg) were significantly higher than in the medium- (17.6 ± 5.2 Kcal/kg, 0.79 ± 0.25 g/kg) and high-risk (17.5 ± 6.1 Kcal/kg, 0.78 ± 0.26 g/kg) groups ( p = 0.001 and p = 0.04 respectively). Relative risk (RR) of malnutrition was less in the low-risk group (103/147, 70.06%) than in the medium-risk group [135/162, 83.3%; RR: 2.0; 95% confidence interval (CI): 2.1 to 3.4; p = 0.01] or the high-risk group (54/64, 84.4%; RR: 2.3; 95% CI: 2.1 to 4.9; p = 0.03). Mean survivals of patients in the low-, medium-, and high-risk groups were 51 patient–months (95% CI: 45.6 to 56.4 patient–months), 43.3 patient–months (95% CI: 37.8 to 48.7 patient–months), and 29.7 patient–months (95% CI: 23 to 36.4 patient–months) respectively (log-rank: 35.9 patient–months; p = 0.001). The 1-, 2-, 3-, 4-, and 5-year patient survivals in the low-, medium-, and high-risk groups were 96%, 87%, 79%, 65%, and 56%; 89%, 67%, 54%, 43%, and 34%; and 76%, 48%, 31%, 30%, and 30% respectively. Conclusions Intake of calories and protein was significantly lower in the medium-risk and high-risk groups than in the low-risk group. Survival was significantly better in low-risk patients than in medium- and high-risk patients.


CJEM ◽  
2017 ◽  
Vol 19 (S1) ◽  
pp. S62
Author(s):  
V. Thiruganasambandamoorthy ◽  
M. Sivilotti ◽  
M.A. Mukarram ◽  
C. Leafloor ◽  
K. Arcot ◽  
...  

Introduction: Concern for occult serious conditions leads to variations in ED syncope management [hospitalization, duration of ED/inpatient monitoring including Syncope Observation Units (SOU) for prolonged monitoring]. We sought to develop evidence-based recommendations for duration of ED/post-ED ECG monitoring using the Canadian Syncope Risk Score (CSRS) by assessing the time to serious adverse event (SAE) occurrence. Methods: We enrolled adults with syncope at 6 EDs and collected demographics, time of syncope and ED arrival, CSRS predictors and time of SAE. We stratified patients as per the CSRS (low, medium and high risk as ≤0, 1-3 and ≥4 respectively). 30-day adjudicated SAEs included death, myocardial infarction, arrhythmia, structural heart disease, pulmonary embolism or serious hemorrhage. We categorized arrhythmias, interventions for arrhythmias and death from unknown cause as arrhythmic SAE and the rest as non-arrhythmic SAE. We performed Kaplan-Meier analysis using time of ED registration for primary and time of syncope for secondary analyses. Results: 5,372 patients (mean age 54.3 years, 54% females, and 13.7% hospitalized) were enrolled with 538 (10%) patients suffering SAE (0.3% died due to an unknown cause and 0.5% suffered ventricular arrhythmia). 64.8% of SAEs occurred within 6 hours of ED arrival. The probability for any SAE or arrhythmia was highest within 2-hours of ED arrival for low-risk patients (0.65% and 0.31%; dropped to 0.54% and 0.06% after 2-hours) and within 6-hours for the medium and high-risk patients (any SAE 6.9% and 17.4%; arrhythmia 6.5% and 18.9% respectively) which also dropped after 6-hours (any SAE 0.99% and 2.92%; arrhythmia 0.78% and 3.07% respectively). For any CSRS threshold, the risk of arrhythmia was highest within the first 15-days (for CSRS ≥2 patients 15.6% vs. 0.006%). ED monitoring for 2-hours (low-risk) and 6-hours (medium and high-risk) and using a CSRS ≥2 cut-off for outpatient 15-day ECG monitoring will lead to 52% increase in arrhythmia detection. The majority (82.2%) arrived to the ED within 2-hours (median time 1.1 hours) and secondary analysis yielded similar results. Conclusion: Our study found 2 and 6 hours of ED monitoring for low-risk and medium/high-risk CSRS patients respectively, with 15-day outpatient ECG monitoring for CSRS ≥2 patients will improve arrhythmia detection without the need for hospitalization or observation units.


2020 ◽  
Author(s):  
Mehmet Akce ◽  
Katerina Zakka ◽  
McKenna Penley ◽  
Renjian Jiang ◽  
Olatunji B. Alese ◽  
...  

Abstract Background: Clinico-pathological high-risk features are frequently utilized in adjuvant chemotherapy (AC) decisions in stage II colorectal cancer and their utility in stage II appendiceal adenocarcinoma (AA) is not established. The aim of this study is to determine the impact of high-risk features in clinical outcomes and whether high risk features are predictive of AC benefit in stage II AA. Methods: Patients with pathological stage II AA between 2010-2015 were identified from the National Cancer Database (NCDB) using ICD-O-3 morphology and topography codes: 8140, 8480 and C18.1. High risk stage II AA was defined as having at least one of the following clinicopathological features: T4 tumor, <12 lymph nodes examined, poorly differentiated histology, positive margins, or lymphovascular invasion. Patients with none of these features were defined as low-risk.Results: A total of 1,040 patients with pathological stage II AA were identified. 51.0% males, 84.5% Caucasian; median age 61 (range, 19-90). 46.4% were determined to have high-risk stage II AA. High-risk status was associated with worse OS compared to low-risk in univariate (HR 1.55; 95% CI 1.18-2.02; p=0.001) and multivariable analyses (HR 1.36; 95% CI 1.03-1.79; p=0.028). High-risk stage II AA patients had significantly worse 5-year OS compared to low-risk patients (67.1% vs. 74.5%, p=0.0013). AC was administered in 34.4% (n=166) of high-risk patients and in 36.5% (n=203) of low-risk patients. Among high-risk patients, AC was not associated with better OS in univariate (HR 0.86; 95% CI 0.59-1.26; p=0.448) and multivariable analyses (HR 1.35; 95% CI 0.90-2.04; p=0.151) compared to no AC. Similarly, among low-risk patients, AC was not associated with better OS in univariate (HR 0.92; 95% CI 0.60-1.39; p=0.679) and multivariable analyses (HR 1.27; 95% CI 0.81-2.02; p=0.299) compared to no AC. For high-risk patients, 5-year OS was 68.3% in patients that received AC vs. 66.5% in patients that did not (p=0.722). For low-risk patients, 5-year OS was 74.0% in patients that received AC vs. 76.3% in patients that did not (p=0.813).Conclusion: High-risk stage II AA patients had significantly worse 5-year OS compared to low-risk patients. AC did not improve survival regardless of high-risk features in stage II AA.


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