The Increasing Burden of Emergency Department and Inpatient Consultations for "Papilledema".

BACKGROUND: Increasing incidence of idiopathic intracranial hypertension (IIH), overreported radiologic signs of intracranial hypertension, difficult access to outpatient neuro-ophthalmology services, poor insurance coverage, and medicolegal concerns have lowered the threshold for emergency department (ED) visits for "papilledema." Our objective was to examine referral patterns and outcomes of neuro-ophthalmology ED and inpatient consultations for concern for papilledema. METHODS: At one university-based quaternary care center, all adults referred for "papilledema" over one year underwent a standardized ED "papilledema protocol." We collected patient demographics, final diagnoses, and referral patterns. RESULTS: Over 1 year, 153 consecutive patients were referred for concern for papilledema. After papilledema protocol, 89 of 153 patients (58%) had bilateral optic disc edema, among whom 89% (79/89) had papilledema (intracranial hypertension). Of the 38 of 153 (25%) consultations for suspected disorder of intracranial pressure without previous fundus examination (Group 1), 74% (28/38) did not have optic disc edema, 21% (8/38) had papilledema, and 5% (2/38) had other causes of bilateral disc edema. Of the 89 of 153 (58%) consultations for presumed papilledema seen on fundus examination (Group 2), 58% (66/89) had confirmed papilledema, 17% (15/89) had pseudopapilledema, and 9% (8/89) had other causes of bilateral optic disc edema. Of the 26 of 153 (17%) patients with known IIH (Group 3), 5 had papilledema and 4 required urgent intervention. The most common diagnosis was IIH (58/79). Compared with IIH, patients with secondary causes of intracranial hypertension were older (P = 0.002), men (P < 0.001), not obese (P < 0.001), and more likely to have neurologic symptoms (P = 0.002). CONCLUSION: Inpatient and ED consultations for "papilledema" are increasing. Of the 153 ED and inpatient neuro-ophthalmology consultations seen for "papilledema" over 1 year, one-third of patients with optic disc edema of unknown cause before presentation to our ED had new vision- or life-threatening disease, supporting the need for prompt identification and evaluation of optic disc edema in the ED. In the face of limited access to neuro-ophthalmologists, this study supports the need for emergency department access to expert eye-care evaluation or ocular fundus camera for prompt identification of optic disc edema and standardized evaluation for neurologic emergencies.

Utilizing logistic regression to compare risk factors in disease modeling with imbalanced data: a case study in vitamin D and cancer incidence.

Imbalanced data, a common challenge encountered in statistical analyses of clinical trial datasets and disease modeling, refers to the scenario where one class significantly outnumbers the other in a binary classification problem. This imbalance can lead to biased model performance, favoring the majority class, and affecting the understanding of the relative importance of predictive variables. Despite its prevalence, the existing literature lacks comprehensive studies that elucidate methodologies to handle imbalanced data effectively. In this study, we discuss the binary logistic model and its limitations when dealing with imbalanced data, as model performance tends to be biased towards the majority class. We propose a novel approach to addressing imbalanced data and apply it to publicly available data from the VITAL trial, a large-scale clinical trial that examines the effects of vitamin D and Omega-3 fatty acid to investigate the relationship between vitamin D and cancer incidence in sub-populations based on race/ethnicity and demographic factors such as body mass index (BMI), age, and sex. Our results demonstrate a significant improvement in model performance after our undersampling method is applied to the data set with respect to cancer incidence prediction. Both epidemiological and laboratory studies have suggested that vitamin D may lower the occurrence and death rate of cancer, but inconsistent and conflicting findings have been reported due to the difficulty of conducting large-scale clinical trials. We also utilize logistic regression within each ethnic sub-population to determine the impact of demographic factors on cancer incidence, with a particular focus on the role of vitamin D. This study provides a framework for using classification models to understand relative variable importance when dealing with imbalanced data.

Neuro-ophthalmology Emergency Department and Inpatient Consultations at a Large Academic Referral Center.

PURPOSE: Prompt neuro-ophthalmology consultation prevents diagnostic errors and improves patient outcomes. The scarcity of neuro-ophthalmologists means that the increasing outpatient demand cannot be met, prompting many emergency department (ED) referrals by non-neuro-ophthalmologists. We describe our quaternary care institution's ED and inpatient neuro-ophthalmology consultation patterns and patient outcomes. DESIGN: Prospective observational study. PARTICIPANTS: Consecutive neuro-ophthalmology ED and inpatient consultation requests over 1 year. METHODS: We collected patient demographics, distance traveled, insurance status, referring provider details, consultation question, final diagnosis, complexity of consultation, time of consultation, and need for outpatient follow-up. MAIN OUTCOME MEASURES: Consultation patterns and diagnoses, complexity, and follow-up. RESULTS: Of 494 consecutive adult ED and inpatient neuro-ophthalmology consultations requested over 1 year, 241 of 494 consultations (49%) occurred at night or during weekends. Of ED consultations (322 of 494 [65%]), 127 of 322 consultations (39%) occurred during weekdays, 126 of 322 consultations (39%) occurred on weeknights, and 69 of 322 consultations (22%) occurred on weekends or holidays. Of 322 ED consultations, 225 of 322 consultations (70%) were patients who initially sought treatment in the ED with a neuro-ophthalmic chief symptom. Of the 196 patients sent to the ED by a health care professional, 148 patients (148/196 [76%]) were referred by eye care specialists (74 optometrists and 74 ophthalmologists). The most common ED referral questions were for papilledema (75 of 322 [23%]) and vision loss (72 of 322 [22%]). A total of 219 of 322 patients (68%) received a final active neuro-ophthalmic diagnosis, 222 of 322 patients (69%) were cases of high or very high complexity, and 143 of 322 patients (44%) required admission. Inpatient consultations (n = 172) were requested most frequently by hospitalists, including neurologists (71 of 172 [41%]) and oncologists (20 of 172 [12%]) for vision loss (43 of 172 [25%]) and eye movement disorders (36 of 172 [21%]) and by neurosurgeons (58 of 172 [33%]) for examination for mass or a preoperative evaluation (19 of 172 [11%]). An active neuro-ophthalmic diagnosis was confirmed in 67% of patients (116 of 172). Outpatient neuro-ophthalmology follow-up was required for 291 of 494 patients (59%). CONCLUSIONS: Neuro-ophthalmology consultations are critical to the diagnosis and management in the hospital setting. In the face of a critical shortage of neuro-ophthalmologists, this study highlights the need for technological and diagnostic aids for greater outpatient access. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

The emergence of lines of hierarchy in collective motion of biological systems.

The emergence of large-scale structures in biological systems, and in particular the formation of lines of hierarchy, is observed at many scales, from collections of cells to groups of insects to herds of animals. Motivated by phenomena in chemotaxis and phototaxis, we present a new class of alignment models that exhibit alignment into lines. The spontaneous formation of such 'fingers' can be interpreted as the emergence of leaders and followers in a system of identically interacting agents. Various numerical examples are provided, which demonstrate emergent behaviors similar to the 'fingering' phenomenon observed in some phototaxis and chemotaxis experiments; this phenomenon is generally known to be a challenging pattern for existing models to capture. A novel protocol for pairwise interactions provides a fundamental alignment mechanism by which agents may form lines of hierarchy across a wide range of biological systems.

Modeling optimal reopening strategies for COVID-19 and its variants by keeping infections low and fixing testing capacity.

Since early March 2020, government agencies have utilized a wide variety of non-pharmaceutical interventions to mitigate the spread of COVID-19 and have struggled to determine when it is appropriate to return to in-person activities after an outbreak is detected. At many universities, fundamental issues related to understanding the spread of the disease (e.g. the transmission rate), the ability of administrators to respond quickly enough by closing when there is a sudden rise in cases, and how to make a decision on when to reopen remains a concern. Surveillance testing strategies have been implemented in some places, and those test outcomes have dictated whether to reopen, to simultaneously monitor community spread, and/or to isolate discovered cases. However, the question remains as to when it is safe to reopen and how much testing is required to remain safely open while keeping infection numbers low. Here, we propose an extension of the classic SIR model to investigate reopening strategies for a fixed testing strategy, based on feedback from testing results. Specifically, we close when a predefined proportion of the population becomes infected, and later reopen when that infected proportion decreases below a predefined threshold. A valuable outcome of our approach is that our reopening strategies are robust to variation in almost all model parameters, including transmission rates, which can be extremely difficult to determine as they typically differ between variants, location, vaccination status, etc. Thus, these strategies can be, in theory, translated over to new variants in different regions of the world. Examples of robust feedback strategies for high disease transmission and a fixed testing capacity include (1) a single long lock down followed by a single long in-person period, and (2) multiple shorter lock downs followed by multiple shorter in-person periods. The utility of this approach of having multiple strategies is that administrators of universities, schools, business, etc. can use a strategy that is best adapted for their own functionality.

Clinical Reasoning: A 55-Year-Old Woman With Recurrent Episodes of Aphasia and Vision Changes.

A 55-year-old woman presented with recurrent episodes of headache, vision changes, and language disturbances. Brain MRI showed multifocal white matter lesions, microhemorrhages, and enlarged perivascular spaces. After an extensive and unrevealing workup, she underwent a biopsy of brain and meninges that revealed thick and hyalinized leptomeningeal and cortical vessel walls that were strongly positive for ß-amyloid by immunohistochemical staining, suggestive of cerebral amyloid angiopathy (CAA). CAA can present as a spectrum of inflammatory responses to the deposition of amyloid-ß in the vessel walls. Her clinical presentation, radiologic, and histopathologic findings supported a diagnosis of probable CAA-related inflammation (CAA-ri). Although an uncommon entity, it is important to recognize it because most patients respond to immunosuppressive therapy.

Universal features of epidemic models under social distancing guidelines.

Social distancing as a form of nonpharmaceutical intervention has been enacted in many countries as a form of mitigating the spread of COVID-19. There has been a large interest in mathematical modeling to aid in the prediction of both the total infected population and virus-related deaths, as well as to aid government agencies in decision making. As the virus continues to spread, there are both economic and sociological incentives to minimize time spent with strict distancing mandates enforced, and/or to adopt periodically relaxed distancing protocols, which allow for scheduled economic activity. The main objective of this study is to reduce the disease burden in a population, here measured as the peak of the infected population, while simultaneously minimizing the length of time the population is socially distanced, utilizing both a single period of social distancing as well as periodic relaxation. We derive a linear relationship among the optimal start time and duration of a single interval of social distancing from an approximation of the classic epidemic SIR model. Furthermore, we see a sharp phase transition region in start times for a single pulse of distancing, where the peak of the infected population changes rapidly; notably, this transition occurs well before one would intuitively expect. By numerical investigation of more sophisticated epidemiological models designed specifically to describe the COVID-19 pandemic, we see that all share remarkably similar dynamic characteristics when contact rates are subject to periodic or one-shot changes, and hence lead us to conclude that these features are universal in epidemic models. On the other hand, the nonlinearity of epidemic models leads to non-monotone behavior of the peak of infected population under periodic relaxation of social distancing policies. This observation led us to hypothesize that an additional single interval social distancing at a proper time can significantly decrease the infected peak of periodic policies, and we verified this improvement numerically. While synchronous quarantine and social distancing mandates across populations effectively minimize the spread of an epidemic over the world, relaxation decisions should not be enacted at the same time for different populations.

A novel COVID-19 epidemiological model with explicit susceptible and asymptomatic isolation compartments reveals unexpected consequences of timing social distancing.

Motivated by the current COVID-19 epidemic, this work introduces an epidemiological model in which separate compartments are used for susceptible and asymptomatic "socially distant" populations. Distancing directives are represented by rates of flow into these compartments, as well as by a reduction in contacts that lessens disease transmission. The dynamical behavior of this system is analyzed, under various different rate control strategies, and the sensitivity of the basic reproduction number to various parameters is studied. One of the striking features of this model is the existence of a critical implementation delay (CID) in issuing distancing mandates: while a delay of about two weeks does not have an appreciable effect on the peak number of infections, issuing mandates even slightly after this critical time results in a far greater incidence of infection. Thus, there is a nontrivial but tight "window of opportunity" for commencing social distancing in order to meet the capacity of healthcare resources. However, if one wants to also delay the timing of peak infections - so as to take advantage of potential new therapies and vaccines - action must be taken much faster than the CID. Different relaxation strategies are also simulated, with surprising results. Periodic relaxation policies suggest a schedule which may significantly inhibit peak infective load, but that this schedule is very sensitive to parameter values and the schedule's frequency. Furthermore, we considered the impact of steadily reducing social distancing measures over time. We find that a too-sudden reopening of society may negate the progress achieved under initial distancing guidelines, but the negative effects can be mitigated if the relaxation strategy is carefully designed.

Ischemic stroke in COVID-19: An urgent need for early identification and management.

OBJECTIVE: In the setting of the Coronavirus Disease 2019 (COVID-19) global pandemic caused by SARS-CoV-2, a potential association of this disease with stroke has been suggested. We aimed to describe the characteristics of patients who were admitted with COVID-19 and had an acute ischemic stroke (AIS). METHODS: This is a case series of PCR-confirmed COVID-19 patients with ischemic stroke admitted to an academic health system in metropolitan Atlanta, Georgia (USA) between March 24th, 2020 and July 17th, 2020. Demographic, clinical, and radiographic characteristics were described. RESULTS: Of 396 ischemic stroke patients admitted during this study period, 13 (2.5%) were also diagnosed with COVID-19. The mean age of patients was 61.6 ± 10.8 years, 10 (76.9%) male, 8 (61.5%) were Black Americans, mean time from last normal was 4.97 ± 5.1 days, and only one received acute reperfusion therapy. All 13 patients had at least one stroke-associated co-morbidity. The predominant pattern of ischemic stroke was embolic with 4 explained by atrial fibrillation. COVID-19 patients had a significantly higher rate of cryptogenic stroke than non-COVID-19 patients during the study period (69% vs 17%, p = 0.0001). CONCLUSIONS: In our case series, ischemic stroke affected COVID-19 patients with traditional stroke risk factors at an age typically seen in non-COVID populations, and mainly affecting males and Black Americans. We observed a predominantly embolic pattern of stroke with a higher than expected rate of cryptogenic strokes, a prolonged median time to presentation and symptom recognition limiting the use of acute reperfusion treatments. These results highlight the need for increased community awareness, early identification, and management of AIS in COVID-19 patients.

Mathematical Details on a Cancer Resistance Model.

One of the most important factors limiting the success of chemotherapy in cancer treatment is the phenomenon of drug resistance. We have recently introduced a framework for quantifying the effects of induced and non-induced resistance to cancer chemotherapy (Greene et al., 2018a, 2019). In this work, we expound on the details relating to an optimal control problem outlined in Greene et al. (2018a). The control structure is precisely characterized as a concatenation of bang-bang and path-constrained arcs via the Pontryagin Maximum Principle and differential Lie algebraic techniques. A structural identifiability analysis is also presented, demonstrating that patient-specific parameters may be measured and thus utilized in the design of optimal therapies prior to the commencement of therapy. For completeness, a detailed analysis of existence results is also included.

Mathematical Approach to Differentiate Spontaneous and Induced Evolution to Drug Resistance During Cancer Treatment.

PURPOSE: Drug resistance is a major impediment to the success of cancer treatment. Resistance is typically thought to arise from random genetic mutations, after which mutated cells expand via Darwinian selection. However, recent experimental evidence suggests that progression to drug resistance need not occur randomly, but instead may be induced by the treatment itself via either genetic changes or epigenetic alterations. This relatively novel notion of resistance complicates the already challenging task of designing effective treatment protocols. MATERIALS AND METHODS: To better understand resistance, we have developed a mathematical modeling framework that incorporates both spontaneous and drug-induced resistance. RESULTS: Our model demonstrates that the ability of a drug to induce resistance can result in qualitatively different responses to the same drug dose and delivery schedule. We have also proven that the induction parameter in our model is theoretically identifiable and propose an in vitro protocol that could be used to determine a treatment's propensity to induce resistance.

Neurohospitalist Practice, Perspectives, and Burnout.

BACKGROUND AND PURPOSE: Neurohospitalist neurology is a fast-growing subspecialty with a variety of practice settings featuring neurohospitalist models of care. Since inception, the subspecialty has responded to new challenges in resident training, hospital reimbursement, practice, and burnout. METHODS: To characterize neurohospitalists' current practice and perspectives, we surveyed the neurohospitalists and trainees affiliated with the Neurohospitalist Society using an electronic survey distributed through the society listserv. RESULTS: Of 501 individuals surveyed by e-mail, 119 began the survey (23.8% response rate), with 88.2% self-identifying as neurohospitalists. Most neurohospitalists (63%) are 10 years or less out of training, devoting 70% of their professional time to inpatient clinical activities while also performing administrative or teaching activities. Only 38% are employed by an academic department. Call schedules are common, with 75% of neurohospitalists participating in a hospital or emergency call schedule, while 55% provide telemedicine services. The majority (97%) of neurohospitalists primarily care for adults, most commonly treating patients with cerebrovascular disease, seizures, and delirium/encephalopathy. The majority (87%) are overall pleased with their work, but 36% report having experienced burnout. CONCLUSIONS: Neurohospitalists are a diverse group of neurologists primarily practicing in the inpatient setting while performing a variety of additional activities. They provide a wide array of clinical expertise for acute neurological diseases and neurological emergencies that require hospitalization, including stroke, seizure, and encephalopathy. Neurohospitalists in general are very pleased with their work, while burnout, as in neurology and other areas of medicine, remains a concern.

Collaborative Comanagement Between Neurohospitalists and Internal Medicine Hospitalists Decreases Provider Costs and Enhances Satisfaction With Neurology Care at an Academic Medical Center.

BACKGROUND AND PURPOSE: The majority of academic medical centers are moving to a neurohospitalist model of care for hospital neurology coverage. Potential benefits over a more traditional academic model of patient care include greater expertise in acute neurologic disease, increased efficiency, and improved availability to patients, providers, and learners. Despite these perceived advantages, switching to a neurohospitalist model can come at substantial financial cost, so finding ways to maximize the positive impact of a limited number of neurohospitalists is very important to the future health of academic neurology departments. Over the past 7 years, we have implemented a model for inpatient neurological care based on an intimate collaborative relationship between the neurology and hospital medicine services at our main academic hospital. Our goal was to optimize the value of care by decreasing cost while improving quality. METHODS: Cost and revenue associated with professional services was evaluated on a yearly basis. As part of ongoing quality improvement efforts, yearly surveys were administered to referring providers during the transition to a collaborative care model in which NHs and medicine hospitalists comanage neurology inpatients. RESULTS: Net operating loss was dramatically decreased upon transition to the new care model. Concomitantly, there was a robust positive impact on perception of overall quality, timeliness, and communication skills of neurology services. CONCLUSIONS: Collaborative comanagement is an effective strategy to improve overall satisfaction with neurology services at a tertiary academic medical center while maintaining financial viability.

An Ex Vivo Platform for the Prediction of Clinical Response in Multiple Myeloma.

Multiple myeloma remains treatable but incurable. Despite a growing armamentarium of effective agents, choice of therapy, especially in relapse, still relies almost exclusively on clinical acumen. We have developed a system, Ex vivo Mathematical Myeloma Advisor (EMMA), consisting of patient-specific mathematical models parameterized by an ex vivo assay that reverse engineers the intensity and heterogeneity of chemosensitivity of primary cells from multiple myeloma patients, allowing us to predict clinical response to up to 31 drugs within 5 days after bone marrow biopsy. From a cohort of 52 multiple myeloma patients, EMMA correctly classified 96% as responders/nonresponders and correctly classified 79% according to International Myeloma Working Group stratification of level of response. We also observed a significant correlation between predicted and actual tumor burden measurements (Pearson r = 0.5658, P < 0.0001). Preliminary estimates indicate that, among the patients enrolled in this study, 60% were treated with at least one ineffective agent from their therapy combination regimen, whereas 30% would have responded better if treated with another available drug or combination. Two in silico clinical trials with experimental agents ricolinostat and venetoclax, in a cohort of 19 multiple myeloma patient samples, yielded consistent results with recent phase I/II trials, suggesting that EMMA is a feasible platform for estimating clinical efficacy of drugs and inclusion criteria screening. This unique platform, specifically designed to predict therapeutic response in multiple myeloma patients within a clinically actionable time frame, has shown high predictive accuracy in patients treated with combinations of different classes of drugs. The accuracy, reproducibility, short turnaround time, and high-throughput potential of this platform demonstrate EMMA's promise as a decision support system for therapeutic management of multiple myeloma. Cancer Res; 77(12); 3336-51. ©2017 AACR.

Translation inhibition and resource balance in the TX-TL cell-free gene expression system.

Quantifying the effect of vital resources on transcription (TX) and translation (TL) helps to understand the degree to which the concentration of each resource must be regulated for achieving homeostasis. Utilizing the synthetic TX-TL system, we study the impact of nucleotide triphosphates (NTPs) and magnesium (Mg2+) on gene expression. Recent observations of the counter-intuitive phenomenon of suppression of gene expression at high NTP concentrations have led to the speculation that such suppression is due to the consumption of resources by TX, hence leaving fewer resources for TL. In this work, we investigate an alternative hypothesis: direct suppression of the TL rate via stoichiometric mismatch in necessary reagents. We observe NTP-dependent suppression even in the early phase of gene expression, contradicting the resource-limitation argument. To further decouple the contributions of TX and TL, we performed gene expression experiments with purified messenger RNA (mRNA). Simultaneously monitoring mRNA and protein abundances allowed us to extract a time-dependent translation rate. Measuring TL rates for different Mg2+ and NTP concentrations, we observe a complex resource dependence. We demonstrate that TL is the rate-limiting process that is directly inhibited by high NTP concentrations. Additional Mg2+ can partially reverse this inhibition. In several experiments, we observe two maxima of the TL rate viewed as a function of both Mg2+ and NTP concentration, which can be explained in terms of an NTP-independent effect on the ribosome complex and an NTP-Mg2+ titration effect. The non-trivial compensatory effects of abundance of different vital resources signal the presence of complex regulatory mechanisms to achieve optimal gene expression.

Mathematical Modeling Reveals That Changes to Local Cell Density Dynamically Modulate Baseline Variations in Cell Growth and Drug Response.

Cell-to-cell variations contribute to drug resistance with consequent therapy failure in cancer. Experimental techniques have been developed to monitor tumor heterogeneity, but estimates of cell-to-cell variation typically fail to account for the expected spatiotemporal variations during the cell growth process. To fully capture the extent of such dynamic variations, we developed a mechanistic mathematical model supported by in vitro experiments with an ovarian cancer cell line. We introduce the notion of dynamic baseline cell-to-cell variation, showing how the emerging spatiotemporal heterogeneity of one cell population can be attributed to differences in local cell density and cell cycle. Manipulation of the geometric arrangement and spatial density of cancer cells revealed that given a fixed global cell density, significant differences in growth, proliferation, and paclitaxel-induced apoptosis rates were observed based solely on cell movement and local conditions. We conclude that any statistical estimate of changes in the level of heterogeneity should be integrated with the dynamics and spatial effects of the baseline system. This approach incorporates experimental and theoretical methods to systematically analyze biologic phenomena and merits consideration as an underlying reference model for cell biology studies that investigate dynamic processes affecting cancer cell behavior. Cancer Res; 76(10); 2882-90. ©2016 AACR.

Weakness in an Elderly Woman With Asthma and Chronic Sinusitis.

Weakness and sensory changes are common complaints in both the inpatient and the outpatient setting. However, this presentation remains a diagnostic challenge to clinicians due to the many possible underlying etiologies. The initial evaluation of weakness and sensory changes starts a thorough history and physical examination to guide the diagnostic process. In this article, we present the case of an elderly woman with complaints of weakness and sensory changes to highlight a step-wise approach to diagnosis and management.

Perioperative Consultation for Patients with Preexisting Neurologic Disorders.

As the population ages, the prevalence of many neurologic diseases is increasing. At the same time, older patients are undergoing more surgical procedures. This confluence of events puts neurohospitalists in a unique position to provide both pre- and postoperative guidance to minimize complications, improve clinical outcomes, and decrease health care costs in patients with neurologic comorbidities. Early preoperative consultation is recommended for patients with severe, poorly controlled, or decompensated neurologic disease, a recent stroke, or those undergoing procedures with a high risk of neurologic complications. The neurohospitalist's role includes optimizing management of preexisting diseases, such as epilepsy, neuromuscular disorders, Parkinson's disease, dementia, and cerebrovascular disease, as well as providing guidance for perioperative management and clarification of risks. In the postoperative period, the neurohospitalist will frequently be consulted to mitigate any negative impact of neurologic complications that do occur.

Modeling intrinsic heterogeneity and growth of cancer cells.

Intratumoral heterogeneity has been found to be a major cause of drug resistance. Cell-to-cell variation increases as a result of cancer-related alterations, which are acquired by stochastic events and further induced by environmental signals. However, most cellular mechanisms include natural fluctuations that are closely regulated, and thus lead to asynchronization of the cells, which causes intrinsic heterogeneity in a given population. Here, we derive two novel mathematical models, a stochastic agent-based model and an integro-differential equation model, each of which describes the growth of cancer cells as a dynamic transition between proliferative and quiescent states. These models are designed to predict variations in growth as a function of the intrinsic heterogeneity emerging from the durations of the cell-cycle and apoptosis, and also include cellular density dependencies. By examining the role all parameters play in the evolution of intrinsic tumor heterogeneity, and the sensitivity of the population growth to parameter values, we show that the cell-cycle length has the most significant effect on the growth dynamics. In addition, we demonstrate that the agent-based model can be approximated well by the more computationally efficient integro-differential equations when the number of cells is large. This essential step in cancer growth modeling will allow us to revisit the mechanisms of multidrug resistance by examining spatiotemporal differences of cell growth while administering a drug among the different sub-populations in a single tumor, as well as the evolution of those mechanisms as a function of the resistance level.