Semiparametric Bayesian inference for optimal dynamic treatment regimes via dynamic marginal structural models.

Considerable statistical work done on dynamic treatment regimes (DTRs) is in the frequentist paradigm, but Bayesian methods may have much to offer in this setting as they allow for the appropriate representation and propagation of uncertainty, including at the individual level. In this work, we extend the use of recently developed Bayesian methods for Marginal Structural Models to arrive at inference of DTRs. We do this (i) by linking the observational world with a world in which all patients are randomized to a DTR, thereby allowing for causal inference and then (ii) by maximizing a posterior predictive utility, where the posterior distribution has been obtained from nonparametric prior assumptions on the observational world data-generating process. Our approach relies on Bayesian semiparametric inference, where inference about a finite-dimensional parameter is made all while working within an infinite-dimensional space of distributions. We further study Bayesian inference of DTRs in the double robust setting by using posterior predictive inference and the nonparametric Bayesian bootstrap. The proposed methods allow for uncertainty quantification at the individual level, thereby enabling personalized decision-making. We examine the performance of these methods via simulation and demonstrate their utility by exploring whether to adapt HIV therapy to a measure of patients' liver health, in order to minimize liver scarring.

Timing social distancing to avert unmanageable COVID-19 hospital surges.

Following the April 16, 2020 release of the Opening Up America Again guidelines for relaxing coronavirus disease 2019 (COVID-19) social distancing policies, local leaders are concerned about future pandemic waves and lack robust strategies for tracking and suppressing transmission. Here, we present a strategy for triggering short-term shelter-in-place orders when hospital admissions surpass a threshold. We use stochastic optimization to derive triggers that ensure hospital surges will not exceed local capacity and lockdowns are as short as possible. For example, Austin, Texas-the fastest-growing large city in the United States-has adopted a COVID-19 response strategy based on this method. Assuming that the relaxation of social distancing increases the risk of infection sixfold, the optimal strategy will trigger a total of 135 d (90% prediction interval: 126 d to 141 d) of sheltering, allow schools to open in the fall, and result in an expected 2,929 deaths (90% prediction interval: 2,837 to 3,026) by September 2021, which is 29% of the annual mortality rate. In the months ahead, policy makers are likely to face difficult choices, and the extent of public restraint and cocooning of vulnerable populations may save or cost thousands of lives.

How did the COVID-19 crisis affect different types of workers in the developing world?

This paper examines how the COVID-19 pandemic affected the employment of different groups of workers across 40 mostly low and middle-income countries. Employment outcomes during the crisis are tracked through high-frequency phone surveys conducted by the World Bank and national statistics offices. Our results show that larger shares of female, young, less educated, and urban workers stopped working at the beginning of the pandemic. Gender gaps in work stoppage stemmed mainly from gender differences within sectors rather than differential employment patterns of men and women across sectors. Differences in work stoppage between urban and rural workers were markedly smaller than those across gender, age, and education groups. Preliminary results from 10 countries suggest that following the initial shock at the start of the pandemic, employment rates partially recovered between April and August 2020, with greater gains for those groups that had borne the brunt of the early jobs losses. Although the high-frequency phone surveys over-represent household heads and therefore overestimate employment rates, a validation exercise for five countries suggests that they provide a reasonably accurate measure of disparities in employment levels by gender, education, and urban/rural location following the onset of the crisis, although they perform less well in capturing disparities between age groups. These results shed new light on the distributional labor market consequences of the COVID-19 crisis in developing countries, and suggest that real-time phone surveys, despite their lack of representativeness, are a valuable source of information to measure differential employment impacts across groups during an unfolding crisis.

Direct health-care costs for children diagnosed with genetic diseases are significantly higher than for children with other chronic diseases.

PURPOSE: We aimed to estimate direct health-care costs and physician utilization for a cohort of children diagnosed with genetic diseases. METHODS: Retrospective cohort study using population-based provincial health administrative data for children with genetic diseases (n = 255) compared with three matched cohorts (asthma n = 1275, diabetes n = 255, general population n = 1275). We estimated direct health-care costs and resource use 5 years after diagnosis in five categories: physician billing, same day surgery, emergency, inpatient hospitalizations, and home care. RESULTS: During the postdiagnostic period, annual mean total costs for the genetic disease cohort were significantly higher than all other cohorts. Annual mean total costs for all cohorts were highest in the year after diagnosis with costs for the genetic disease cohort between 4.54 and 19.76 times higher during the 5 years. Inpatient hospitalizations and physician billing accounted for the majority of costs. The genetic disease cohort received more care from specialists, whereas the chronic disease cohorts received more care from general practitioners. CONCLUSION: Direct health-care costs for children with genetic diseases are significantly higher than children with/without a chronic disease, particularly in the year after diagnosis. These findings are important when considering resource allocation and funding prioritization for children with genetic diseases.

Changing Rates of Self-Harm and Mental Disorders by Sex in Youths Presenting to Ontario Emergency Departments: Repeated Cross-Sectional Study.

OBJECTIVE: To document the rates of intentional self-harm and mental disorders among youths aged 13 to 17 years visiting Ontario emergency departments (EDs) from 2003-2017. METHODS: This was a repeated cross-sectional observational design. Outcomes were rates of adolescents with (1) at least 1 self-harm ED visit and (2) a visit with a mental disorder code. RESULTS: Rates of youths with self-harm visits fell 32% from 2.6/1000 in 2003 to 1.8 in 2009 but rose 135% to 4.2 by 2017. The slope of the trend in self-harm visits changed from -0.18 youths/1000/year (confidence interval [CI], -0.24 to -0.13) during 2003 to 2009 to 0.31 youths/1000/year (CI, 0.27 to 0.35) during 2009 to 2017 (P < 0.001). Rates of youths with mental health visits rose from 11.7/1000 in 2003 to 13.5 in 2009 (15%) and to 24.1 (78%) by 2017. The slope of mental health visits changed from 0.22 youths/1000/year (CI, 0.02 to 0.42) during 2003 to 2009 to 1.84 youths/1000/year (CI, 1.38 to 2.30) in 2009 to 2017 (P < 0.001). Females were more likely to have self-harm (P < 0.001) and mental health visits (P < 0.001). Rates of increase after 2009 were greater for females for both self-harm (P < 0.001) and mental health (P < 0.001). CONCLUSIONS: Rates of adolescents with self-harm and mental health ED visits have increased since 2009, with greater increases among females. Research is required on the determinants of adolescents' self-harm and mental health ED visits and how they can be addressed in that setting. Sufficient treatment resources must be supplied to address increased demands for services.

Effect modification of perinatal exposure to air pollution and childhood asthma incidence.

Perinatal exposure to ambient air pollution has been associated with childhood asthma incidence, however, less is known regarding the potential effect modifiers in this association. We examined whether maternal and infant characteristics modified the association between perinatal exposure to air pollution and development of childhood asthma.761 172 births occurring between 2006 and 2012 were identified in the province of Ontario, Canada. Associations between exposure to ambient air pollutants and childhood asthma incidence (up to age 6) were estimated using Cox regression models.110,981 children with asthma were identified. In models adjusted for postnatal exposures, second trimester exposures to particulate matter with a diameter ≤2.5 µm (PM2.5) (Hazard Ratio (HR) per interquartile (IQR) increase=1.07, 95% CI: 1.06-1.09) and nitrogen dioxide (NO2) (HR per IQR increase=1.06, 95% CI: 1.03-1.08) were associated with childhood asthma development. Enhanced impacts were found among children born to mothers with asthma, those who smoked during pregnancy, boys, those born preterm, of low birth weight and among those born to mothers living in urban areas during pregnancy.Prenatal exposure to air pollution may have a differential impact on the risk of asthma development according to maternal and infant characteristics.

Annual Trends in Follow-Up Visits for Pediatric Concussion in Emergency Departments and Physicians' Offices.

OBJECTIVE: To assess whether children and youth with concussion receive follow-up visits in accordance with the recommended guidelines. STUDY DESIGN: We conducted a retrospective, population-based study using linked health administrative data from all concussion-related visits to emergency department and physician offices by children aged 5 through 18 years (range, 5.00-18.99) in Ontario between 2003 and 2013. We analyzed the percentage of children and youth seen for follow-up. The Mann-Kendall test for trends was used to assess a monotonic increasing trend over time in concussion follow-up visits. RESULTS: A total of 126 654 children and youth were evaluated for an index concussion visit. The number of children and youth assessed for concussion follow-up (N = 45 155) has increased significantly over time (P < .001). In 2003, 781 of 7126 patients (11.0%; 95% CI, 10.3-11.7) with an index visit for concussion had a follow-up assessment. By 2013, 6526 of 21 681 (30.1%; 95% CI, 29.5-30.7) patients received follow-up care. CONCLUSIONS: The proportion of children and youth receiving follow-up after an acute concussion has significantly increased between 2003 and 2013. Nevertheless, more than two-thirds of all patients do not seek medical follow-up or clearance as recommended by current concussion guidelines, suggesting that ongoing efforts to improve and monitor compliance with recommended guidelines by patients and physicians are important.

Annual and Seasonal Trends in Ambulatory Visits for Pediatric Concussion in Ontario between 2003 and 2013.

OBJECTIVE: To investigate annual and seasonal trends in physician office and emergency department (ED) visit rates for pediatric concussion in Ontario between 2003 and 2013. STUDY DESIGN: A retrospective, population-based study was conducted using linked health administrative data from all concussion-related visits to ED and physician office by children aged 5 through 18 years. Time series analysis was used to assess whether periodic components exist in the monthly number of concussion-related visits. RESULTS: Over the 11-year study period, there were 176 685 pediatric visits for concussion in EDs and physician offices in Ontario. Standardized concussion-related visits showed a 4.4-fold (95% CI 4.37-4.45) increase per 100 000 from 2003 to 2013, with nearly 35 000 total visits in 2013. Concussion-related visits demonstrated a steep increase from 2010 onward. The greatest increases in standardized visits were in females (6.3-fold, 95% CI 6.23-6.46 vs 3.6-fold, 95% CI 3.56-3.64 in males) and 13-18.99 year olds (5.0-fold, 95% CI 4.93-5.08 vs 4.1-fold, 95% CI 3.99-4.27 in 9-12 years and 2.3-fold, 95% CI 2.23-2.42 in 5-8 years). A strong seasonal variability (R2autoreg = 0.87, P < .01) in the number of concussion-related visits was present, with most occurring in fall and winter. CONCLUSIONS: Pediatric concussion-related ED and physician office visit rates have greatly increased in the last decade, particularly since 2010. Prevention strategies may be targeted at those most at risk and at seasonal-related activities carrying the greatest risk of concussion.

On the preventive management of sediment-related sewer blockages: a combined maintenance and routing optimization approach.

In this work we tackle the problem of planning and scheduling preventive maintenance (PM) of sediment-related sewer blockages in a set of geographically distributed sites that are subject to non-deterministic failures. To solve the problem, we extend a combined maintenance and routing (CMR) optimization approach which is a procedure based on two components: (a) first a maintenance model is used to determine the optimal time to perform PM operations for each site and second (b) a mixed integer program-based split procedure is proposed to route a set of crews (e.g., sewer cleaners, vehicles equipped with winches or rods and dump trucks) in order to perform PM operations at a near-optimal minimum expected cost. We applied the proposed CMR optimization approach to two (out of five) operative zones in the city of Bogotá (Colombia), where more than 100 maintenance operations per zone must be scheduled on a weekly basis. Comparing the CMR against the current maintenance plan, we obtained more than 50% of cost savings in 90% of the sites.

Deviance detection in auditory subcortical structures: what can we learn from neurochemistry and neural connectivity?

A remarkable ability of animals that is critical for survival is to detect and respond to to unexpected stimuli in an ever-changing world. Auditory neurons that show stimulus-specific adaptation (SSA), i.e., a decrease in their response to frequently occurring stimuli while maintaining responsiveness when different stimuli are presented, might participate in the coding of deviance occurrence. Traditionally, deviance detection is measured by the mismatch negativity (MMN) potential in studies of evoked local field potentials. We present a review of the state-of-the-art of SSA in auditory subcortical nuclei, i.e., the inferior colliculus and medial geniculate body of the thalamus, and link the differential receptor distribution and neural connectivity of those regions in which extreme SSA has been found. Furthermore, we review both SSA and MMN-like responses in auditory and non-auditory areas that exhibit multimodal sensitivities that we suggest conform to a distributed network encoding for deviance detection. The understanding of the neurochemistry and response similarities across these different regions will contribute to a better understanding of the neural mechanism underlying deviance detection.

Modulation of stimulus-specific adaptation by GABA(A) receptor activation or blockade in the medial geniculate body of the anaesthetized rat.

Stimulus-specific adaptation (SSA), which describes adaptation to repeated sounds concurrent with the maintenance of responsiveness to uncommon ones, may be an important neuronal mechanism for the detection of and attendance to rare stimuli or for the detection of deviance. It is well known that GABAergic neurotransmission regulates several different response properties in central auditory system neurons and that GABA is the major inhibitory neurotransmitter acting in the medial geniculate body (MGB). The mechanisms underlying SSA are still poorly understood; therefore, the primary aim of the present study was to examine what role, if any, MGB GABAergic circuits play in the generation and/or modulation of SSA. Microiontophoretic activation of GABA(A) receptors (GABA(A)Rs) with GABA or with the selective GABA(A)R agonist gaboxadol significantly increased SSA (computed with the common SSA index, CSI) by decreasing responses to common stimuli while having a lesser effect on responses to novel stimuli. In contrast, GABA(A)R blockade using gabazine resulted in a significant decrease in SSA. In all cases, decreases in the CSI during gabazine application were accompanied by an increase in firing rate to the stimulus paradigm. The present findings, in conjunction with those of previous studies, suggest that GABA(A)-mediated inhibition does not generate the SSA response, but can regulate the level of SSA sensitivity in a gain control manner. The existence of successive hierarchical levels of processing through the auditory system suggests that the GABAergic circuits act to enhance mechanisms to reduce redundant information.

Dithiocarb (N,N-diethyldithiocarbamate, DEDTC) decreases levels of biogenic monoamines in the adult mouse brain.

AIMS: Dithiocarb (diethyldithiocarbamate, DEDTC) belongs to the group of dithiocarbamates and is the main metabolite of disulphiram, a drug of choice for the treatment of alcohol dependence. Its therapeutic potential relays on its ability to create an unpleasant aversive reaction following the ingestion of alcohol, and this effect is usually accompanied by neurobehavioural symptoms. Most of these can be attributed to the impaired metabolism of brain biogenic amines. METHODS: To gain new insights into the dithiocarbamates and their effects on neurotransmitter systems, an in vivo experimental model based on daily injections of DEDTC in adult mice for 7 days was established. To this end, the concentrations of the three major brain monoamines, dopamine (DA), noradrenaline (NA) and serotonin (5-HT) were measured in whole brain extracts with high-performance liquid chromatography (HPLC). The levels of D2 dopamine receptor (D2R) were evaluated by Western blot and by immunohistochemical techniques the cell pattern of tyrosine hydroxylase (TH), dopa beta hydroxylase (DBH) and choline acetyltransferase ChAT) were analysed. RESULTS: A significant reduction in DA and 5-HT levels was observed, whereas NA was not affected. Moreover, decreases in D2R levels, as well as in enzymes such as TH, DBH and ChAT, were found. CONCLUSIONS: Our data suggest that DEDTC provokes alterations in biogenic amines and in different substrates of neurotransmitter systems, which could explain some of the neurobehavioural effects observed in patients treated with disulphiram.

Temporal Coherence Shapes Cortical Responses to Speech Mixtures in a Ferret Cocktail Party.

Segregation of complex sounds such as speech, music and animal vocalizations as they simultaneously emanate from multiple sources (referred to as the "cocktail party problem") is a remarkable ability that is common in humans and animals alike. The neural underpinnings of this process have been extensively studied behaviorally and physiologically in non-human animals primarily with simplified sounds (tones and noise sequences). In humans, segregation experiments utilizing more complex speech mixtures are common; but physiological experiments have relied on EEG/MEG/ECoG recordings that sample activity from thousands of neurons, often obscuring the detailed processes that give rise to the observed segregation. The present study combines the insights from animal single-unit physiology with segregation of speech-like mixtures. Ferrets were trained to attend to a female voice and detect a target word, both in presence or absence of a concurrent, equally salient male voice. Single neuron recordings were obtained from primary and secondary ferret auditory cortical fields, as well as frontal cortex. During task performance, representation of the female words became more enhanced relative to those of the (distractor) male in all cortical regions, especially in the higher auditory cortical field. Analysis of the temporal and spectral response characteristics during task performance reveals how speech segregation gradually emerges in the auditory cortex. A computational model evaluated on the same voice mixtures replicates and extends these results to different attentional targets (attention to female or male voices). These findings are consistent with the temporal coherence theory whereby attention to a target voice anchors neural activity in cortical networks hence binding together channels that are coherently temporally-modulated with the target, and ultimately forming a common auditory stream.

Topographic distribution, frequency, and intensity dependence of stimulus-specific adaptation in the inferior colliculus of the rat.

The ability to detect unexpected sounds within the environment is an important function of the auditory system, as a rapid response may be required for the organism to survive. Previous studies found a decreased response to repetitive stimuli (standard), but an increased response to rare or less frequent sounds (deviant) in individual neurons in the inferior colliculus (IC) and at higher levels. This phenomenon, known as stimulus-specific adaptation (SSA) has been suggested to underpin change detection. Currently, it is not known how SSA varies within a single neuron receptive field, i.e., it is unclear whether SSA is a unique property of the neuron or a feature that is frequency and/or intensity dependent. In the present experiments, we used the common SSA index (CSI) to quantify and compare the degree of SSA under different stimulation conditions in the IC of the rat. We calculated the CSI at different intensities and frequencies for each individual IC neuron to map the neuronal CSI within the receptive field. Our data show that high SSA is biased toward the high-frequency and low-intensity regions of the receptive field. We also find that SSA is better represented in the earliest portions of the response, and there is a positive correlation between the width of the frequency response area of the neuron and the maximum level of SSA. The present data suggest that SSA in the IC is not mediated by the intrinsic membrane properties of the neurons and instead might be related to an excitatory and/or inhibitory input segregation.

Bayesian inference for optimal dynamic treatment regimes in practice.

In this work, we examine recently developed methods for Bayesian inference of optimal dynamic treatment regimes (DTRs). DTRs are a set of treatment decision rules aimed at tailoring patient care to patient-specific characteristics, thereby falling within the realm of precision medicine. In this field, researchers seek to tailor therapy with the intention of improving health outcomes; therefore, they are most interested in identifying optimal DTRs. Recent work has developed Bayesian methods for identifying optimal DTRs in a family indexed by ψ via Bayesian dynamic marginal structural models (MSMs) (Rodriguez Duque D, Stephens DA, Moodie EEM, Klein MB. Semiparametric Bayesian inference for dynamic treatment regimes via dynamic regime marginal structural models. Biostatistics; 2022. (In Press)); we review the proposed estimation procedure and illustrate its use via the new BayesDTR R package. Although methods in Rodriguez Duque D, Stephens DA, Moodie EEM, Klein MB. (Semiparametric Bayesian inference for dynamic treatment regimes via dynamic regime marginal structural models. Biostatistics; 2022. (In Press)) can estimate optimal DTRs well, they may lead to biased estimators when the model for the expected outcome if everyone in a population were to follow a given treatment strategy, known as a value function, is misspecified or when a grid search for the optimum is employed. We describe recent work that uses a Gaussian process ( G P ) prior on the value function as a means to robustly identify optimal DTRs (Rodriguez Duque D, Stephens DA, Moodie EEM. Estimation of optimal dynamic treatment regimes using Gaussian processes; 2022. Available from: https://doi.org/10.48550/arXiv.2105.12259). We demonstrate how a G P approach may be implemented with the BayesDTR package and contrast it with other value-search approaches to identifying optimal DTRs. We use data from an HIV therapeutic trial in order to illustrate a standard analysis with these methods, using both the original observed trial data and an additional simulated component to showcase a longitudinal (two-stage DTR) analysis.

Recurrent networks endowed with structural priors explain suboptimal animal behavior.

The strategies found by animals facing a new task are determined both by individual experience and by structural priors evolved to leverage the statistics of natural environments. Rats quickly learn to capitalize on the trial sequence correlations of two-alternative forced choice (2AFC) tasks after correct trials but consistently deviate from optimal behavior after error trials. To understand this outcome-dependent gating, we first show that recurrent neural networks (RNNs) trained in the same 2AFC task outperform rats as they can readily learn to use across-trial information both after correct and error trials. We hypothesize that, although RNNs can optimize their behavior in the 2AFC task without any a priori restrictions, rats' strategy is constrained by a structural prior adapted to a natural environment in which rewarded and non-rewarded actions provide largely asymmetric information. When pre-training RNNs in a more ecological task with more than two possible choices, networks develop a strategy by which they gate off the across-trial evidence after errors, mimicking rats' behavior. Population analyses show that the pre-trained networks form an accurate representation of the sequence statistics independently of the outcome in the previous trial. After error trials, gating is implemented by a change in the network dynamics that temporarily decouple the categorization of the stimulus from the across-trial accumulated evidence. Our results suggest that the rats' suboptimal behavior reflects the influence of a structural prior that reacts to errors by isolating the network decision dynamics from the context, ultimately constraining the performance in a 2AFC laboratory task.

Multi-variate model of T cell clonotype competition and homeostasis.

Diversity of the naive T cell repertoire is maintained by competition for stimuli provided by self-peptides bound to major histocompatibility complexes (self-pMHCs). We extend an existing bi-variate competition model to a multi-variate model of the dynamics of multiple T cell clonotypes which share stimuli. In order to understand the late-time behaviour of the system, we analyse: (i) the dynamics until the extinction of the first clonotype, (ii) the time to the first extinction event, (iii) the probability of extinction of each clonotype, and (iv) the size of the surviving clonotypes when the first extinction event takes place. We also find the probability distribution of the number of cell divisions per clonotype before its extinction. The mean size of a new clonotype at quasi-steady state is an increasing function of the stimulus available to it, and a decreasing function of the fraction of stimuli it shares with other clonotypes. Thus, the probability of, and time to, extinction of a new clonotype entering the pool of T cell clonotypes is determined by the extent of competition for stimuli it experiences and by its initial number of cells.

Understanding the use/non-use of an internet-based intervention complementing standard depression treatment: A qualitative study of user's experiences.

Introduction: There is sufficient evidence about the effectiveness of internet-based interventions; however, the users' level of adoption and utilization remains low, with this phenomenon requiring adequate explanation. Objective: The aim of this qualitative study was to explore the users' perceptions and experience of a web-based program (ASCENSO), designed to complement (usual) in-person depression treatment. Method: Twelve participants of the ASCENSO program, comprised of adult individuals (M = 44.3, SD = 13.4) of both genders (67% women) undergoing treatment for depression, were interviewed through semi-structured interviews. The data obtained from these interviews were analyzed utilizing a constructivist grounded theory approach. The interviews were transcribed and analyzed by trained coders. A constant comparative analysis of emergent themes was conducted. Results: These show that users employ and appreciate the program when their interaction with it emulates a "humanized relationship," that is, when the program is proactive in assisting users with their requests and when it responds in a pertinent and individualized manner to their emotional states and needs. Conclusions: Our findings highlight the challenges associated with the development of algorithms capable of attracting different potential users. These should be designed to generate a virtual relationship that emulates human interaction and targets the characteristics of each user, for example, considering the specific phenomenology of their health condition, their present emotional states, and perceived needs. Elements that will vary as mental symptomatology evolve.

Translational Bioinformatics Applied to the Study of Complex Diseases.

Translational Bioinformatics (TBI) is defined as the union of translational medicine and bioinformatics. It emerges as a major advance in science and technology by covering everything, from the most basic database discoveries, to the development of algorithms for molecular and cellular analysis, as well as their clinical applications. This technology makes it possible to access the knowledge of scientific evidence and apply it to clinical practice. This manuscript aims to highlight the role of TBI in the study of complex diseases, as well as its application to the understanding and treatment of cancer. An integrative literature review was carried out, obtaining articles through several websites, among them: PUBMED, Science Direct, NCBI-PMC, Scientific Electronic Library Online (SciELO), and Google Academic, published in English, Spanish, and Portuguese, indexed in the referred databases and answering the following guiding question: "How does TBI provide a scientific understanding of complex diseases?" An additional effort is aimed at the dissemination, inclusion, and perpetuation of TBI knowledge from the academic environment to society, helping the study, understanding, and elucidating of complex disease mechanics and their treatment.

Prognostic Factors and Markers in Non-Small Cell Lung Cancer: Recent Progress and Future Challenges.

Lung cancer is a highly aggressive neoplasm and, despite the development of recent therapies, tumor progression and recurrence following the initial response remains unsolved. Several questions remain unanswered about non-small cell lung cancer (NSCLC): (1) Which patients will actually benefit from therapy? (2) What are the predictive factors of response to MAbs and TKIs? (3) What are the best combination strategies with conventional treatments or new antineoplastic drugs? To answer these questions, an integrative literature review was carried out, searching articles in PUBMED, NCBI-PMC, Google Academic, and others. Here, we will examine the molecular genetics of lung cancer, emphasizing NSCLC, and delineate the primary categories of inhibitors based on their molecular targets, alongside the main treatment alternatives depending on the type of acquired resistance. We highlighted new therapies based on epigenetic information and a single-cell approach as a potential source of new biomarkers. The current and future of NSCLC management hinges upon genotyping correct prognostic markers, as well as on the evolution of precision medicine, which guarantees a tailored drug combination with precise targeting.