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Hazard Ratio
In survival analysis, the hazard ratio (HR) is the ratio of the hazard rates corresponding to the conditions characterised by two distinct levels of a treatment variable of interest. For example, in a clinical study of a drug, the treated population may die at twice the rate of the control population. The hazard ratio would be 2, indicating a higher hazard of death from the treatment. To illustrate how hazard ratio is linked to projected risk: in a population where the incidence of a disease is 10% by age 65 (eg: Dementia), a hazard ratio of 4.42 (eg: Aripiprazole medication) results in an expected incidence of 37.3% by age 65. For example, a scientific paper might use an HR to state something such as: "Adequate COVID-19 vaccination status was associated with significantly decreased risk for the composite of severe COVID-19 or mortality with a[n] HR of 0.20 (95% CI, 0.17–0.22)." In essence, the hazard for the composite outcome was 80% lower among the vaccinated relative to tho ...
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Survival Analysis
Survival analysis is a branch of statistics for analyzing the expected duration of time until one event occurs, such as death in biological organisms and failure in mechanical systems. This topic is called reliability theory, reliability analysis or reliability engineering in engineering, duration analysis or duration modelling in economics, and event history analysis in sociology. Survival analysis attempts to answer certain questions, such as what is the proportion of a population which will survive past a certain time? Of those that survive, at what rate will they die or fail? Can multiple causes of death or failure be taken into account? How do particular circumstances or characteristics increase or decrease the probability of survival? To answer such questions, it is necessary to define "lifetime". In the case of biological survival, death is unambiguous, but for mechanical reliability, failure may not be well-defined, for there may well be mechanical systems in which failure ...
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Sample (statistics)
In this statistics, quality assurance, and survey methodology, sampling is the selection of a subset or a statistical sample (termed sample for short) of individuals from within a population (statistics), statistical population to estimate characteristics of the whole population. The subset is meant to reflect the whole population, and statisticians attempt to collect samples that are representative of the population. Sampling has lower costs and faster data collection compared to recording data from the entire population (in many cases, collecting the whole population is impossible, like getting sizes of all stars in the universe), and thus, it can provide insights in cases where it is infeasible to measure an entire population. Each observation measures one or more properties (such as weight, location, colour or mass) of independent objects or individuals. In survey sampling, weights can be applied to the data to adjust for the sample design, particularly in stratified samplin ...
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Survival Function
The survival function is a function that gives the probability that a patient, device, or other object of interest will survive past a certain time. The survival function is also known as the survivor function or reliability function. The term ''reliability function'' is common in engineering while the term ''survival function'' is used in a broader range of applications, including human mortality. The survival function is the complementary cumulative distribution function of the lifetime. Sometimes complementary cumulative distribution functions are called survival functions in general. Definition Let the lifetime T be a continuous random variable describing the time to failure. If T has cumulative distribution function F(t) and probability density function f(t) on the interval [0,\infty), then the ''survival function'' or ''reliability function'' is: S(t) = P(T > t) = 1-F(t) = 1 - \int_0^t f(u)\,du Examples of survival functions The graphs below show examples of hypot ...
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Relapse
In internal medicine, relapse or recidivism is a recurrence of a past (typically medical) condition. For example, multiple sclerosis and malaria often exhibit peaks of activity and sometimes very long periods of dormancy, followed by relapse or recrudescence. In psychiatry, relapse or reinstatement of drug-seeking behavior, is the recurrence of pathological drug use, self harm or other symptoms after a period of recovery. Relapse is often observed in individuals who have developed a drug addiction or a form of drug dependence, as well as those who have a mental disorder. Risk factors Dopamine D2 receptor availability The availability of the dopamine receptor D2 plays a role in self-administration and the reinforcing effects of cocaine and other stimulants. The D2 receptor availability has an inverse relationship to the vulnerability of reinforcing effects of the drug. With the D2 receptors becoming limited, the user becomes more susceptible to the reinforcing effects of coc ...
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Selection Bias
Selection bias is the bias introduced by the selection of individuals, groups, or data for analysis in such a way that proper randomization is not achieved, thereby failing to ensure that the sample obtained is representative of the population intended to be analyzed. It is sometimes referred to as the selection effect. The phrase "selection bias" most often refers to the distortion of a statistical analysis, resulting from the method of collecting samples. If the selection bias is not taken into account, then some conclusions of the study may be false. Types of bias Sampling bias Sampling bias is systematic error due to a non-random sample of a population, causing some members of the population to be less likely to be included than others, resulting in a biased sample, defined as a statistical sample of a statistical population, population (or non-human factors) in which all participants are not equally balanced or objectively represented. It is mostly classified as a subtype of ...
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Late Effect
In medicine, a late effect is a condition that appears after the acute phase of an earlier, causal condition has run its course. A late effect can be caused directly by the earlier condition, or by the treatment for the earlier condition. Some late effects can occur decades later. Historically, late effects have been very difficult to connect with their causes, but as survival and life span have increased and "follow up" has become standard practice, these connections are becoming established. A period, often very long, of health unaffected by both the initial and the late effect conditions distinguishes a late effect from a sequela or a complication. A code for such a condition was present in the ICD-9 but is no longer present in the ICD-10. Examples * Chickenpox may be followed decades later by herpes zoster: see herpes zoster. * Chemotherapy, radiation therapy and surgery to cure a cancer may result years later in another, unrelated cancer and/or infertility or subfertility: ...
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Adverse Effects
An adverse effect is an undesired harmful effect resulting from a medication or other intervention, such as surgery. An adverse effect may be termed a "side effect", when judged to be secondary to a main or therapeutic effect. The term complication is similar to adverse effect, but the latter is typically used in pharmacological contexts, or when the negative effect is expected or common. If the negative effect results from an unsuitable or incorrect dosage or procedure, this is called a medical error and not an adverse effect. Adverse effects are sometimes referred to as "iatrogenic" because they are generated by a physician/treatment. Some adverse effects occur only when starting, increasing or discontinuing a treatment. Using a drug or other medical intervention which is contraindicated may increase the risk of adverse effects. Adverse effects may cause complications of a disease or procedure and negatively affect its prognosis. They may also lead to non-compliance with a t ...
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Complication (medicine)
A complication in medicine, or medical complication, is an unfavorable result of a disease, health condition, or therapy, treatment. Complications may adversely affect the prognosis, or outcome, of a disease. Complications generally involve a worsening in the severity of the disease or the development of new signs, symptoms, or pathology, pathological changes that may become widespread throughout the body and affect other organ systems. Thus, complications may lead to the development of new diseases resulting from previously existing diseases. Complications may also arise as a result of various treatments. The development of complications depends on a number of factors, including the degree of vulnerability, susceptibility, senescence, age, health status, and immune system condition. Knowledge of the most common and severe complications of a disease, procedure, or treatment allows for prevention and preparation for treatment if they should occur. Complications are not to be confus ...
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1 (number)
1 (one, unit, unity) is a number, numeral, and glyph. It is the first and smallest positive integer of the infinite sequence of natural numbers. This fundamental property has led to its unique uses in other fields, ranging from science to sports, where it commonly denotes the first, leading, or top thing in a group. 1 is the unit of counting or measurement, a determiner for singular nouns, and a gender-neutral pronoun. Historically, the representation of 1 evolved from ancient Sumerian and Babylonian symbols to the modern Arabic numeral. In mathematics, 1 is the multiplicative identity, meaning that any number multiplied by 1 equals the same number. 1 is by convention not considered a prime number. In digital technology, 1 represents the "on" state in binary code, the foundation of computing. Philosophically, 1 symbolizes the ultimate reality or source of existence in various traditions. In mathematics The number 1 is the first natural number after 0. Each natural ...
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Regression Coefficient
In statistics, linear regression is a model that estimates the relationship between a scalar response (dependent variable) and one or more explanatory variables (regressor or independent variable). A model with exactly one explanatory variable is a ''simple linear regression''; a model with two or more explanatory variables is a multiple linear regression. This term is distinct from multivariate linear regression, which predicts multiple correlated dependent variables rather than a single dependent variable. In linear regression, the relationships are modeled using linear predictor functions whose unknown model parameters are estimated from the data. Most commonly, the conditional mean of the response given the values of the explanatory variables (or predictors) is assumed to be an affine function of those values; less commonly, the conditional median or some other quantile is used. Like all forms of regression analysis, linear regression focuses on the conditional probab ...
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Standard Deviation
In statistics, the standard deviation is a measure of the amount of variation of the values of a variable about its Expected value, mean. A low standard Deviation (statistics), deviation indicates that the values tend to be close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the values are spread out over a wider range. The standard deviation is commonly used in the determination of what constitutes an outlier and what does not. Standard deviation may be abbreviated SD or std dev, and is most commonly represented in mathematical texts and equations by the lowercase Greek alphabet, Greek letter Sigma, σ (sigma), for the population standard deviation, or the Latin script, Latin letter ''s'', for the sample standard deviation. The standard deviation of a random variable, Sample (statistics), sample, statistical population, data set, or probability distribution is the square root of its variance. (For a finite population, v ...
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Statistical Significance
In statistical hypothesis testing, a result has statistical significance when a result at least as "extreme" would be very infrequent if the null hypothesis were true. More precisely, a study's defined significance level, denoted by \alpha, is the probability of the study rejecting the null hypothesis, given that the null hypothesis is true; and the p-value, ''p''-value of a result, ''p'', is the probability of obtaining a result at least as extreme, given that the null hypothesis is true. The result is said to be ''statistically significant'', by the standards of the study, when p \le \alpha. The significance level for a study is chosen before data collection, and is typically set to 5% or much lower—depending on the field of study. In any experiment or Observational study, observation that involves drawing a Sampling (statistics), sample from a Statistical population, population, there is always the possibility that an observed effect would have occurred due to sampling error al ...
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