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AMA Research Challenge 2022

MSIDx: Pan-cancer detection of microsatellite instability through targeted microsatellite sequencing enables immunotherapy

Welcome to the largest national, multi-specialty research event **featuring research from 750 medical students, residents and fellows, and international medical graduates.**


#### Event Details
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At the conclusion of this event, the AMA will announce the top five finalists who will advance to the AMA Research Challenge finals, present their research to an elite panel of judges and compete to win a $10,000 grand prize sponsored by Laurel Road.
 

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Ricardo Correa, MD, EdD
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Stuart M. Greenstein, MD
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Stephanie Strohbeen, MD
 
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Jessica Li, MD/PhD Candidate
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Charles Lopresto, DO

### Sponsor
AMA would like to thank Laurel Road for sponsoring a $10,000 grand prize for the winner of the AMA Research Challenge. Laurel Road is not involved in the judging or scoring process to select the winner. The winner will be announced on Dec. 7 during the AMA Research Challenge finals. Payment of the grand prize will be directly from Laurel Road. See the AMA Research Challenge Official Rules for terms and conditions.

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Welcome to the largest national, multi-specialty research event featuring research from 750 medical students, residents and fellows, and international medical graduates.


poster

Abstract Title: Non-responder prediction in patients with advanced urothelial carcinoma using machine learning.

Background: Post FDA approval immunotherapy for cancer becomes widely used for locally advanced or metastatic urothelial carcinomas (1) with 16.5% of patients suffering Grade 3-5 side effects (2) from treatment. The current investigation wanted to classify patients that will not respond to immune checkpoint inhibitors (ICI) and potentially prevent side effects for these patients.

Methods: Pretreatment normalized ribonucleic acid Sequencing (RNASeq), clinical and other data for patients with advanced UC receiving PD-1 axis inhibitors were downloaded from gene expression omnibus (GEO) datasets project PRJNA735749 (3). This data also included responses to treatment data. Responders were categorized as patients with either complete response (CR), partial response (PR), or stable disease (SD) while non-responders comprised patients with progressive disease (PD). With a 70/30 training/test data split we developed four distinct algorithms were developed using a complete or targeted gene expression profile (high vs low expression with non-RNASeq data; total mutational burden (TMB), clinical data, and FGFR mutational status. The performance of each of the algorithms was assessed by comparing a matric of test set accuracy, sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV), and area under the receiver-operating curves.

Results: A total of 89 patients (from a total of 103) had complete RNASeq, DNA, and clinical data. The complete RNASeq + non-RNASeq data showed test set; accuracy (18.5%), sensitivity (100%), specificity (0.0%), PPV (25%), NPV (UD*). The targeted RNASeq + non-RNA Seq data showed test set; accuracy (70.4%), sensitivity (0.0%), specificity (100%), PPV (undefined), NPV (70.4%). The targeted RNASeq (Hi/Low cutoff) + non- RNASeq data using a Multilayer Perceptron (MLP) classifier showed test set; accuracy (81.5%), sensitivity (20.0%), specificity (95.5%), PPV (50.0%), NPV (84.0%). The targeted RNASeq (Hi/Low cutoff) + non-RNASeq data using a TensorFlow (TF) classifier showed test set; accuracy (77.8%), sensitivity (20.0%), specificity (90.9%), PPV (33.3%), NPV (83.3%).

Conclusion: The MLP/deep-learning classifier for targeted normalized high vs low RNA expression with TMB, clinical characteristics, and FGFR mutational status shows better overall results compared to other algorithms. However, these results need external validation and with a larger dataset and we may also be able to predict responders in these patients.


Non-responder prediction in patients with advanced urothelial carcinoma using machine learning

Background 
In patients diagnosed with cancer, pain can interfere with daily functioning, affecting overall quality of life. The predictors of pain in patients with cancer are not well-delineated. Further, pain has been associated with inflammation, yet previous research attempting to understand this link has been limited secondary to the lack of inclusion of other covariates associated with inflammation. The aims of this study were to describe pain intensity and interference in patients with cancer, investigate the predictors and consequences of pain, and examine the associations between pain and cytokines while covarying factors associated with inflammation. 

Methods
This study was a secondary analysis of baseline data from three prospective studies conducted between 2008-2019 at the University of Pittsburgh Medical Center Cancer Center. Patients completed questionnaires assessing sociodemographic characteristics, pain, depression, sleep, and fatigue. Serum levels of cytokines IL-1alpha, IL-1beta, TNF-alpha, IL-10, IL-2, and IFN-gamma were assessed. Analyses of Variance, Chi-square analyses, and linear regression were performed to test the hypotheses. 


Results
Of the 779 participants, the mean age was 63.5 years (S.D.=11.02), 57.8% male, 90.6% Caucasian. 67.3% of patients reported pain, of which 50.4% of patients reported was cancer-related. Significant predictors of pain intensity and interference included lower education level (beta=-2.800, 95% CI=[-4.374,-1.227], p=0.01) and a diagnosis of hepatocellular carcinoma or cholangiocarcinoma (beta=-0.947, 95% CI=[-1.551,-0.343], p=0.002). After adjusting for sociodemographic, disease-specific, and treatment-related factors, pain significantly predicted higher levels of depression (beta=0.587, 95% CI=[0.425,0.749], p<0.001), fatigue (beta=-0.858, 95% CI=[-1.031,-0.684], p<0.001), and fewer hours of sleep per night (beta=-0.055, 95% CI=[-0.088,-0.023], p=0.001). After adjusting for sociodemographic, disease-specific, and treatment-related factors, pain was not significantly related to serum levels of IL-1alpha, IL-1beta, TNF-alpha, IL-10, IL-2, or IFN-gamma.

Conclusion
Nearly one-third of patients reported cancer-related pain, which was linked to poorer quality of life. Pain, however, was not found to be associated with inflammatory biomarkers, warranting further research into underlying biological mechanisms of pain and related symptoms of depression, fatigue, and poor sleep. Given that pain predictors included lower education level and diagnosis of liver cancer, interventions should be designed and implemented for these patients with the greatest need for pain management.

Pain, Inflammation, and Psychosocial Factors in the Context of Cancer

Predictors of hematologic response and survival with stem cell transplantation in patients with AL amyloidosis: a 25-year longitudinal study

Background: RT recipients have a 5-6-fold increased risk of renal cell carcinoma (RCC). Post-RT RCCs usually arise from the native kidneys but may rarely develop in the allograft. We analyzed the incidence and clinical outcomes of patients with RA RCC at Memorial Hermann Hospital, Texas Medical Center.

Methods: We performed a single center retrospective study of patients with RA RCC who underwent transplantation between January 1, 1999, and December 31, 2019. The following data were collected: Baseline demographic variables, cause of end stage renal disease (ESRD), duration of dialysis prior to RT, interval from RT to RCC diagnosis, RCC stage, histologic subtype, and clinical outcome post RCC treatment.

Results: Among 1998 RT recipients, 7 patients (0.3%) developed RCC in the RA, of whom 4 were men. Subject races included White (n=3), Black (n=2), Hispanic (n=1), and Asian (n=1). The median age was 56 years (Range, 18-66). Causes of ESRD included diabetic or hypertensive nephropathy (n=3), congenital renal dysplasia (n=1), Alport syndrome (n=1), IgA nephropathy (n=1) and Henoch Schoenlein purpura (n=1). Median duration of dialysis prior to RT was 48 months (range, 1–120). Median time to RCC diagnosis post-RT was 108 months (range, 48-180). Histologies included clear cell (n=5) and papillary (n=2) RCC. Majority (n=6) were nonsmokers. 
Six patients (85%) had stage I disease and all of them had deterioration in renal function that prompted renal imaging and biopsy that led to RCC diagnosis. One patient had stage IV disease at diagnosis and presented with hematuria. All seven patients had evidence of chronic allograft nephropathy. One patient had BK Virus nephropathy in the allograft. Six patients underwent transplant nephrectomy while one had cryotherapy. Three patients went back on dialysis while three patients underwent a retransplantation. None had RCC recurrence post retransplantation. Three patients died: 1 each with sepsis, COVID 19 and metastatic RCC.

Conclusion: Although rare, RA RCC can adversely affect long term survival. Chronic inflammation in the setting of RA nephropathy and iatrogenic immunosuppression are believed to be the main driving factors. 



Renal Allograft (RA) Renal Cell Carcinoma in Renal Transplant (RT) Recipients: A Single Center Retrospective Review

Abstract Title:
Does definitive local therapy have a role in select HER2+de novo metastatic breast cancer patients treated with dual anti HER2 blockade?

Background:
The role of surgery with curative intent in HER2+de novo metastatic breast cancer (dnMBC) is uncertain in the era of dual antibody therapy. We sought to determine from existing retrospective data current practice patterns if an association exists between surgery to the primary tumor and improved survival in HER2+dnMBC patients treated with dual anti-HER2 blockade, accounting for selection bias.

Methods:
This study employed data from the National Cancer Database (NCDB) from the years 2013 to 2015. Study inclusion was limited to adult women with HER2+dnMBC, who received immunotherapy/biologic response modifier drugs (BRM) as a first line treatment. Patients who received both systemic therapy and surgery to the primary breast tumor and patients who received systemic therapy alone were analyzed in two groups. Chi-square test for discrete variables and Wilcox on RankSum test for numeric variables was used to compare the two groups based on patient, tumor, and treatment characteristics. The primary endpoint was overall survival from the time of diagnosis to the time of death.

Results:
928 women with HER2+dnMBC treated with BRM were identified with 43.5% (n=404) receiving surgery and 56.5% (n=524) receiving systemic therapy alone. The 3-year overall survival was superior for the surgery group (74.1%, 95% CI 67.9–79.2%) compared to the no surgery group (53.3%; 95% CI 47.6–58.6%). The no surgery group had median overall survival of 39.8 months (95% CI 34.1–44.9), while the surgery group had not yet reached median overall survival.

Conclusion:
In a group of HER2+dnMBC patients receiving systemic treatment in the era of dual antibody therapy, patients who underwent surgery had a superior 3-year survival rate than those who did not. There may be a role for a prospective trial in HER2+dnMBC patients with an excellent response to dual HER2 blockade to investigate the contribution of curative intent local therapy to the primary tumor compared to systemic therapy alone.


Should we operate?: The role of surgery in HER2+ de novo metastatic breast cancer treated with dual anti-HER2+ blockade

Background
Adolescent and Young Adult (AYA) cancer patients have been historically understudied. Many improvements in survival observed for pediatric and older adult patients have not been paralleled in the AYA population. Contributing factors of this discrepancy may involve unique challenges AYA patients face, including poor investigative research, limited access to care, or financial insecurity. Several studies have identified that these challenges disproportionally impact AYA patients belonging to racial minority and lower socioeconomic (SES) groups, thus leading to worsened survival outcomes. We aimed to investigate differences in survival among AYA patients of different races, ethnicities, and SES treated within the same health care system, Kaiser Permanente Southern California (KPSC).

Methods
We identified patients, aged 15-39, diagnosed with the fourteen most common cancers in this age group at KPSC between the years 2010-2018, yielding 6,463 patients. Cancers included were breast, testis, leukemia, Non-Hodgkin and Hodgkin lymphoma, melanoma, colon, cervical, uterine, renal, brain, soft tissue, rectosigmoid, ovarian, stomach, and bone. The Neighborhood Deprivation Index (NDI), a validated measure of socioeconomic deprivation obtained from geocoded data of home addresses, was used as a marker of SES. Race, ethnicity, and survival data were obtained from the Electronic Health Record. We examined differences in survival rates for all cancer types, and breast cancer and leukemia separately, for NDI quartiles and racial and ethnic groups. 

Results
Patients residing in the two most deprived areas have a higher all-cause mortality rate compared to those living in the two least deprived areas for all cancer types combined (p=0.0012). We did not detect a significant difference in survival rate between different NDI groups for patients with leukemia. White patients, compared to non-White patients, had statistically significant improved survival rates (p=0.0000036) for all cancer types combined. Black and Hispanic patients with leukemia had lower survival rates than Asian/Pacific Islander and White subjects with leukemia (p=0.0052). No difference was found among breast cancer patients of different NDI quartiles or races/ethnicities.

Conclusion
Patients experiencing higher levels of deprivation have lower survival rates compared to less deprived patients. White patients had significantly higher survival rates than Black, Hispanic, or Asian/Pacific Islander patients for all cancer types combined.


Socioeconomic and Racial Disparities in Survival for Adolescent and Young Adult Cancer Patients

Background

Staging is devised to assess prognosis and direct the management of cancers. Although staging systems don't necessarily confirm chronological progression, there is near consensus that advanced stages are 'later' versions of a given cancer. Tumor Mutational Burden (TMB) is a metric measuring proliferative state, representing a “molecular clock” (Vogelstein) of sorts and a surrogate for chronology. TMB is commonly provided to oncologists as essential clinical data, however proper interpretation is still evolving. We hypothesized that (i) advanced-stage is a qualitative rather than chronologic indicator, (ii) proliferation rates will be mirrored in TMB, and (iii) TMB will correlate with clinical virulence.


Methods

(i) We mined the TCGA database (cbioportal.org) for incremental increases in TMB relative to increasing neoplasm clinical stage from 558 samples (Breast, Colon, Renal cell, Pancreatic, Cervical). (ii) We compared the TMB in Burkitt's with follicular lymphoma representing lymphoma proliferative spectrum. (iii) We compared the TMB in cutaneous squamous carcinoma (CSC) with Acute Myelogenous Leukemia, representing indolent versus aggressive malignancies, respectively.


Results

(i) The 95% Confidence Intervals (CI) surrounding the median TMB were overlapping without statistical significance across all stages within every histology examined. (ii) To our surprise, the TMB 95% CI were overlapping between the 2 subsets of B-cell lymphoma examined. (iii) TMB was substantially higher in CSC (median of ~800) compared with 8 in AML.


Conclusion

Assuming the validity of Vogelstein’s molecular clock model, mutational probing does not support the concept that a stage IV malignancy is a chronologically delayed manifestation of a given neoplasm. Rather, we suggest that aggressive/metastatic cancers are inherently 'different' with unique abilities. We also posit that cells that live for years (follicular lymphoma) can accumulate comparable TMB levels as Burkitt's because the limited life span in Burkitt's (days to weeks) precludes the accumulation of high TMB. Finally, a malignancy’s clinical outcome cannot be discerned from the degree or mutability— which is rationally a predictor of immune susceptibility. It's noteworthy that the observed levels of mutations in CSC, reflective of sun-induced mutagenicity, is more than 3-fold of that reported for melanoma (~274) and may explain the rarity of metastatic CSC resulting from immune clearance of metastases.

Validity of Mutations as a Cancer Chronometer

Background
Multiple Myeloma (MM) has been associated with extensive morbidity and mortality in hospitalized patients. MM has been considered a treatable disease entity with the advent of novel therapeutics. Vitamin D deficiency (VDD) affects 1 in 7 individuals worldwide and is a key element in bone modulation. In this study, we aim to provide greater clarity on the relationship between VDD and MM and outcomes of VDD amongst multiple myeloma patients.
Methods
We performed a retrospective cross-sectional study using HCUP data from 2016 to 2018. Patients with MM and VDD were identified using ICD 10 codes. We used SAS 9.4 for univariate analyses (unpaired student’s t-test and chi-square test) and multivariate survey regression analysis to evaluate demographic characteristics, epidemiology, the association between VDD and MM, and outcomes of patients with VDD. Adjusted odds ratio and 95% confidence interval were calculated and sensitivity index (C-index) was obtained. A P-value less than 0.05 was considered significant.
Results
Analysis revealed 330,175 patients had multiple myeloma out of 11,480 (0.035%) had VDD. VDD was more common in the middle age group (50-75 years: 3.6% vs >75 years: 3.3%), female (4.1% vs male: 2.9%), Asian-Pacific Islander race (3.8% vs Black: 3.5% vs White: 3.5% vs Hispanics: 3.2%), and median household income 75-100 percentile (3.8% vs 0-25 percentile: 3.4%), Midwest or North Central region states (4.5% vs Northeast: 3.3%), patients with obese 4.6% vs non-obese: 3.4%, dyslipidemia 4.1% vs non-dyslipidemia: 3.1%, renal failure 3.5% vs non-failure: 3.4%, AIDS 4% vs non-AIDS: 3.5%, and alcohol abuse 4.1% vs no-abuse: 3.5%. Prevalence of morbidity (5.1% vs 3.9%; p<0.0001) and disability (77.2% vs 73.3%; p<0.0001) were higher amongst patients with VDD in comparison without VDD amongst MM. In regression analysis, prevalence odds of VDD were significantly higher (aOR 1.41, 95%CI: 1.35-1.47, p<.0001, c=0.636) in patients with MM in comparison without MM. We also found that VDD patients were associated with 24% higher morbidity (1.24, 1.14-1.36, p<.0001, c=0.667) and 26% higher disability (1.26, 1.20-1.33, p<.0001, c=0.725).
Conclusion
There was a significant association between VDD and MM with a significant increase in morbidity and disability in patients with concurrent VDD and MM. The vast array of actions of vitamin D in various cellular pathways yields a dramatic effect on patient outcomes in MM. It is imperative to treat VDD to improve clinical outcomes in patients with MM.

A steep fall to high morbidity and disability; Vitamin D deficiency in Multiple Myeloma Patients.

Comprehensive evaluation of acute management and blood pressure response in 1596 minority patients with very severe hypertension (>220/>120 mmHg)

Abstract Title: Higher odds of the Utilization of Thrombolysis and MACCE events in Acute Kidney Injury Associated with Pulmonary Embolism: A Nationwide study
Karnav Modi, MBBS, and Akhil Jain, MD

Background
Pulmonary thromboembolism (PTE) is an acute life-threatening condition with a mortality rate of up to 65% in high-risk patients. Clinical outcomes in these patients, including mortality, are influenced by multiple factors. One such factor is acute kidney damage (AKI), a frequent complication in hospitalized patients and also known to have poorer prognoses. However, the utilization of thrombolytic therapies and frequency of major adverse cardiovascular and cerebrovascular events (MACCE) in acute pulmonary embolism (PE) patients with AKI has been poorly investigated. Therefore, this study sought to evaluate the frequency and odds of outcomes and the utilization rates of various lines of therapies in PE patients with AKI.

Methods
We used the 2019 National Inpatient Sample (NIS) dataset to identify patients with a primary discharge diagnosis of PE without acute cor pulmonale. Next, they were grouped into two cohorts based on the presence of Acute Kidney Injury (AKI). We used descriptive statistics to compare demographics, hospital-related characteristics, and comorbidities amongst two cohorts. Lastly, we used Pearson’s chi-square to identify the differences in outcomes and developed a multivariate regression model to obtain adjusted odds ratios (aOR) and incidence rate ratios (IRR) for outcomes and utilization of therapies amongst the two cohorts.


Results
Among the 170,955 patients hospitalized with acute PE, 13.8% patients (n=23,610) had AKI. AKI cohort had older (mean age 68.2 vs. 62.6 years) and more male (54.4%) patients. AKI cohort had a significantly higher rate and odds of mortality (9.9% vs. 1.9%; aOR 3.0, 95% CI: 2.6-3.5, P<0.001), mean length of stay (LOS) (6.3 vs. 3.9 days, P<0.001), and mean total cost of hospitalization (81528.7 vs. 44324.3 USD, P<0.001). Among both cohorts, inferior vena cava (IVC) filter had the highest utilization rate (7.2% vs. 4.1%, P<0.001), followed by systemic thrombolysis (4.6% vs. 1.7%, P<0.001), catheter-directed thrombolysis (CDT) (3.7% vs. 2.4%, P<0.001), and surgical embolectomy (0.021% vs. 0.007%, P=0.327). Following adjustment, the AKI cohort had higher odds of the utilization of CDT (aOR 1.6, 95% CI: 1.3-2.0, P<0.001), systemic thrombolysis (aOR 2.0, 95% CI: 1.6-2.4, P<0.001), and IVC filter (aOR 1.4, 95% CI: 1.2-1.6, P<0.001). AKI cohort had a significantly higher incidence and odds for MACCE events (a composite of death, myocardial infarction, and stroke) (17.2% vs. 5.4%; aOR 2.3, 95% CI: 2.1- 2.6, P<0.001).


Conclusion
AKI in acute PE tends to have a poorer prognosis and higher odds of mortality, MACCE events, use of IVC filter, and thrombolytic therapies, with systemic thrombolysis being used more frequently than CDT in AKI patients. In addition, AKI accounts for significantly higher utilization of hospital resources due to longer LOS and higher total cost of hospitalization

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Non-responder prediction in patients with advanced urothelial carcinoma using machine learning

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