Hazard Ratio
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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 per unit time of the control population. The hazard ratio would be 2, indicating higher hazard of death from the treatment. A scientific paper might utilise a Hazard Ratio (HR) to state something as follows. "Adequate COVID-19 vaccination status was associated with significantly decreased risk for the composite of severe COVID-19 or mortality with a HR of 0.20 (95% CI, 0.17-0.22)." In layman's English, this means: People in the study who were vaccinated were 20% as likely to get severe Covid-19 or to die, compared to people who weren't vaccinated in the same study. So, for a hazardous outcome (e.g. death), a Hazard Ratio below 1 indicates that the treatment (e.g. vaccination) might be favorable (less hazardous ...
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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 or reliability analysis 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 is partial, a matter of ...
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Log-rank Test
The logrank test, or log-rank test, is a hypothesis test to compare the survival distributions of two samples. It is a nonparametric test and appropriate to use when the data are right skewed and censored (technically, the censoring must be non-informative). It is widely used in clinical trials to establish the efficacy of a new treatment in comparison with a control treatment when the measurement is the time to event (such as the time from initial treatment to a heart attack). The test is sometimes called the Mantel–Cox test. The logrank test can also be viewed as a time-stratified Cochran–Mantel–Haenszel test. The test was first proposed by Nathan Mantel and was named the ''logrank test'' by Richard and Julian Peto. Definition The logrank test statistic compares estimates of the hazard functions of the two groups at each observed event time. It is constructed by computing the observed and expected number of events in one of the groups at each observed event time and t ...
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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 or reliability analysis 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 is partial, a matter of ...
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Clinical Significance
In medicine and psychology, clinical significance is the practical importance of a treatment effect—whether it has a real genuine, palpable, noticeable effect on daily life. Types of significance Statistical significance Statistical significance is used in hypothesis testing, whereby the null hypothesis (that there is no relationship between variables) is tested. A level of significance is selected (most commonly ''α'' = 0.05 or 0.01), which signifies the probability of incorrectly rejecting a true null hypothesis. If there is a significant difference between two groups at ''α'' = 0.05, it means that there is only a 5% probability of obtaining the observed results under the assumption that the difference is entirely due to chance (i.e., the null hypothesis is true); it gives no indication of the magnitude or clinical importance of the difference. When statistically significant results are achieved, they favor rejection of the null hypothesis, but they do not prove that the nul ...
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Statistical Hypothesis Testing
A statistical hypothesis test is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis. Hypothesis testing allows us to make probabilistic statements about population parameters. History Early use While hypothesis testing was popularized early in the 20th century, early forms were used in the 1700s. The first use is credited to John Arbuthnot (1710), followed by Pierre-Simon Laplace (1770s), in analyzing the human sex ratio at birth; see . Modern origins and early controversy Modern significance testing is largely the product of Karl Pearson ( ''p''-value, Pearson's chi-squared test), William Sealy Gosset ( Student's t-distribution), and Ronald Fisher ("null hypothesis", analysis of variance, "significance test"), while hypothesis testing was developed by Jerzy Neyman and Egon Pearson (son of Karl). Ronald Fisher began his life in statistics as a Bayesian (Zabell 1992), but Fisher soon grew disenchanted with t ...
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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 with cumulative distribution function ''F''(''t'') on the interval [0,∞). Its ''survival function'' or ''reliability function'' is: :S(t) = P(\) = \int_t^ f(u)\,du = 1-F(t). Examples of survival functions The graphs below show examples of hypothetical survival functions. The x-axis is time. The y-axis is the proportion o ...
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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 coca ...
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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 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 population (or non-human factors) in which all participants are not equally balanced or objectively represented. It is mostly classified as a subtype of selection bias, sometimes sp ...
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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 indirectly 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 survivorship and life span has 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 infertility or sub ...
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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. Adverse effects can also be caused by placebo treatments (in which case the adverse effects are referred to as nocebo effects). Using a drug or other medical intervention which is contraindicated may increase the risk of adverse effects. Adverse effects may c ...
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Complication (medicine)
A complication in medicine, or medical complication, is an unfavorable result of a disease, health condition, or treatment. Complications may adversely affect the prognosis, or outcome, of a disease. Complications generally involve a worsening in severity of disease or the development of new signs, symptoms, or pathological changes which may become widespread throughout the body and affect other organ systems. Thus, complications may lead to the development of new diseases resulting from a previously existing disease. 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, age, health status, and immune system condition. Knowledge of the most common and severe complications of a disease, procedure, or treatment allow for prevention and preparation for treatment if they should occur. Complications are not to be confused with sequelae, which are residual ...
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1 (number)
1 (one, unit, unity) is a number representing a single or the only entity. 1 is also a numerical digit and represents a single unit of counting or measurement. For example, a line segment of ''unit length'' is a line segment of length 1. In conventions of sign where zero is considered neither positive nor negative, 1 is the first and smallest positive integer. It is also sometimes considered the first of the infinite sequence of natural numbers, followed by  2, although by other definitions 1 is the second natural number, following  0. The fundamental mathematical property of 1 is to be a multiplicative identity, meaning that any number multiplied by 1 equals the same number. Most if not all properties of 1 can be deduced from this. In advanced mathematics, a multiplicative identity is often denoted 1, even if it is not a number. 1 is by convention not considered a prime number; this was not universally accepted until the mid-20th century. Additionally, 1 is ...
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