BBH 440 rest of semester info

cancer and 5 year survival rates

- 5-year survival rates are an indication of what proportion of patients diagnosed with a particular type of cancer survived 5 years after diagnosis. It doesn't matter if they were cancer-free at that 5-year mark, or still very sick—5-year survival rates only measure survival, regardless of the individual's condition at the 5-year point. - 5-year survival generally depends a great deal on the stage of cancer an individual was diagnosed with. For example, stage I breast cancer has a 5-year survival rate of 98%; however, for breast cancer that has metastasized (stage IV), the survival rate drops down to 23%. You can see from the figures below that some cancers have generally higher 5-year survival rates while others have generally lower rates. In the figures, the heading "local" refers to cancer that remains in the organ it originated in, "regional" refers to cancer that has spread to neighboring organs, and "distant" refers to cancer that has metastasized and spread to distant organs. This is another approach to cancer staging. Although there is no precise equivalent, it would be fair to say that "local"=stage I, "regional"=stage II-III, and "distant"=stage IV.

Time trends in cancer

- Cancer mortality rates have fluctuated over the course of the twentieth and into the twenty-first century. For most of the twentieth century, deaths due to cancer slowly increased. Then, beginning in the 1990s, cancer deaths began to decline gradually. Like the decline in cardiovascular disease mortality we discussed in the last section, the decline in cancer mortality is likely attributable to improvements in primary, secondary, and tertiary prevention. - You can see from these graphs that how successful we seem to have been in the war against cancer depends on which cancer we are talking about. Our efforts against colon and rectum cancer, for example, seem to be paying off. Colon cancer rates have been either relatively stable or gradually declining for much of the twentieth century; they began to decline much more rapidly in the latter part of the twentieth century. This was to a large degree due to the advent of effective methods for colon cancer screening. - ung cancer rates over the last 50 years, however, display more of a fluctuating pattern. You can see that lung cancer mortality rates in men began to increase dramatically around the middle of the twentieth century. This rise represents the increase in smoking rates that began near the end of the first half of the twentieth century. For women, you can see that lung cancer mortality increased as well—although not as drastically—but the increase began later in the century than it did for men. This is due in large part to the fact that smoking was less socially acceptable for women than it was for men around this time. It became more acceptable for women over time, but the fact that fewer women smoked than men is reflected in a lower overall mortality rate for women. Both rates began to decline in the latter half of the twentieth century when the risks of smoking became clear and it became widely understood that smoking was dangerous. Interestingly, the decline in women's rates follows the same gradual slope that was seen in the increase in women's rates.

Gestational diabetes

- Gestational diabetes only affects pregnant women. It involves a temporary disruption in how the body secretes and/or responds to insulin, which occurs during pregnancy. This condition may disappear after the pregnancy, but it also is associated with an increased risk of the woman developing type 2 diabetes after pregnancy. It also is linked to a number of negative effects on the fetus' health.

Pre-diabetes

- Individuals with prediabetes have not been diagnosed with diabetes, nor are they diagnosable based on blood glucose levels. They do, however, have higher than normal blood glucose levels (just not quite high enough to yet be diagnosed with diabetes). These individuals are at a greater risk of developing type 2 diabetes in the near future, however, so epidemiologists have begun to collect data on them as a group to focus primary prevention on

Type 2 diabetes

- Individuals with type 2 diabetes mellitus often produce enough insulin (at least in the early stages of the disease), but the cells of their bodies have stopped responding properly to insulin; this is called insulin resistance. Type 2 diabetes is often diagnosed later than type 1 diabetes, causing it to sometimes be referred to as adult-onset diabetes.

Stroke belt

- One interesting aberration in cardiovascular disease epidemiology was discovered in the 1960s by researchers at the CDC, who noticed that a grouping of 11 southeastern states (Alabama, Arkansas, Georgia, Indiana, Kentucky, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, and Virginia) had stroke mortality rates that were more than 10% greater than the national average. The regions included in the stroke belt also have higher than normal rates of other types of cardiovascular disease. - It is unclear what the causes underlying the high rates of cardiovascular disease in the stroke belt are. Some have attributed them to dietary practices in these southern states, which involve high consumption of fried and high-fat foods. Others have blamed high smoking rates. And others have suggested that the rural nature of many areas in the stroke belt means health care is less adequate for many individuals here, and thus they are less likely to benefit from primary prevention efforts. It is probable, however, that there are several contributing factors that have led to the formation of the stroke belt, and not one overriding reason for its existence.

complications of diabetes

- Patients with diabetes can experience a number of symptoms due to hyperglycemia. - For example, the cells of their body do not get enough glucose, so the patient can begin to feel weak and even hungry (because their body is sending a signal that more glucose needs to be taken in). But hyperglycemia also is thought to have a damaging effect on blood vessels, which can lead to not only other symptoms but also more serious—and potentially life-threatening—complications. - High blood sugar is associated with damage to blood vessels. This vascular damage increases the risk of cardiovascular disease, possibly by acting as the damage that initiates atherosclerosis. Because of these factors, individuals with diabetes are 2-4 times more likely to die from cardiovascular disease than those without diabetes, and close to 70% of individuals with diabetes over the age of 65 die from heart disease of some type. Diabetes itself is thus a major risk factor for heart disease. - Diabetes' ability to damage blood vessels can affect a variety of other organs and functions. When the blood vessels that supply the retina of the eye are damaged, a person may experience visual disturbances or even blindness. Blurred and/or double vision are often experienced by diabetics, and diabetes is the leading cause of new cases of blindness. - Hyperglycemia can also lead to damage to the kidneys, which in the later stages of diabetes might cause impaired kidney function. Kidney disease caused by diabetes is the most common cause of kidney failure. - High blood sugar is associated with damage to the nerves throughout the body. This damage begins with damage to the blood vessels that supply these nerves. When the nerves are damaged, a patient may experience abnormal sensations like tingling or burning, or a loss of sensation altogether. This is known as diabetic neuropathy.

Cancer staging

- Stage 0: While the cells in this stage are abnormal, they are still growing only in their site of origination and have not yet formed a tumor. These cells are generally not considered "cancerous," but there is an increased likelihood the area will become cancerous. - Stage I, II, and III: These stages all describe a cancerous tumor. The higher the number, the larger the tumor is and the more it has spread from its site of origin into neighboring tissues. What specifically warrants a designation of stage I, II, or III often depends on the type of cancer in question. - Stage IV: The cancer has metastasized and spread from its site of origination to tissues it distant areas of the body.

How to interpret a likelihood ratio

- The interpretation of the likelihood ratio is similar in some ways to the interpretation of the odds ratio and relative risk. If a positive or negative likelihood ratio is equal to 1.0, then it means the test is uninformative. In other words, it means that the test is returning false results at a rate similar to the true results it returns. - The further a positive likelihood ratio gets above 1.0, the more informative the test is. If a positive likelihood ratio is 10 or greater, it is considered strong evidence that a positive screening test is actually representative of disease. - The further a negative likelihood ratio gets below 1.0 (in decimals, not negative numbers), the more informative the test is. If a negative likelihood ratio is 0.10 or lower, it is considered strong evidence that a negative screening test actually represents a lack of disease.

what are statistics good for?

- Whenever you hear news report talk about the number of current cases of a disease, you will know that they are actually referring to the disease's prevalence. And you will have a deeper understanding of what such a statistic means, what it is influenced by, and what its limitations are. - your understanding of these statistics will give you a more in-depth appreciation for the background considerations that go into a statistic you might hear bandied about on the news. You may also now have a better understanding of how such statistics might be misinterpreted or exaggerated.

Non-modifiable risk factors (Cardiovascular disease)

- age - sex - race - family history

Non modifiable risk factors for Cancer

- age - sex (men more likely) - Race (black more likely) - Family history

Non-modifiable risk factors for diabetes

- age (20% over age of 65) - sex (higher in men) - race (hispanic and black higher risk) - Family history

Modifiable risk factors for Cancer

- carcinogens - overweight and obesity - physical activity - diet

Modifiable risk factors (cardiovascular disease)

- hypertension - overweight and obesity - high cholesterol - dietary fat - smoking, alcohol consumption, type 2 diabetes

type 1 diabetes

- insulin dependent. pancreas can't make insulin - Type 1 diabetes mellitus is caused by a depletion of the insulin-producing cells in the pancreas. It is thought this reduction in insulin-producing cells is due to an autoimmune attack on these cells. Type 1 diabetes usually is diagnosed at a relatively young age (but it can be diagnosed at any age). Individuals with type 1 diabetes will usually at some point become dependent on administered insulin (e.g. through insulin injections).

Diabetes prevention program - methods of study and what it found

- investigated the efficacy of different interventions in reducing the risk of developing type 2 diabetes. The DPP was a randomized clinical trial that involved over 3,000 participants who were at a high risk for developing type 2 diabetes. They were overweight and/or obese (the average BMI was 34—an obese BMI is 30 or above) and they had high glucose levels (but not high enough to be diagnosed with diabetes, making them prediabetic). - In group one, the participants engaged in what was termed "intensive lifestyle change." These changes involved physical activity for 150 minutes a week and a low-fat diet. The goal was to reduce body weight by 7%. - In group two, participants received what was called "standard advice" about diet and exercise. In other words, they were told what any doctor might tell a patient who has a high risk of developing diabetes---that eating better, becoming more physically active, and losing weight might help them to reduce their risk. In addition to this standard advice they were also given a medication called metformin. Metformin is a popular medication for the treatment of type 2 diabetes. It inhibits the production of glucose in the liver, reducing blood glucose levels. - In group three, participants received the same standard advice as group 2 but they were given a placebo instead of metformin. - Researchers followed up with the individuals for an average of three years to determine which was more effective in reducing the risk of developing type 2 diabetes: an intense lifestyle intervention or a medication that is commonly used to treat diabetes. The results may surprise you. - The group that received metformin (group two) was 31% less likely to develop type 2 diabetes than the placebo group (group 3). The group that received the lifestyle intervention (group 1), however, was 58% less likely than the placebo group (group 3) to develop type 2 diabetes. - The DPP study thus underscored the importance of lifestyle modifications in reducing the risk of diabetes. The results were important for clinicians and epidemiologists, as they inspired more confidence in their recommendations of exercise and diet as a way to prevent diabetes.

Time trends (cardiovascular disease)

- leading cause of death every year since 1910 - Mortality rates from cardiovascular disease reached a peak in the 1960s and then began to steadily decline. Although still the leading cause of death in 2016, we have seen the rates of cardiovascular disease gradually decrease over the latter half of the twentieth century and into the twenty-first. This is due primarily to improvements in understanding cardiovascular disease, which have led to better primary, secondary, and tertiary prevention.

Cardiovascular disease

- number one leading cause of death = umbrella term; refers to variety of diseases - hypertension is most prevalent, CAD and stroke have biggest impact on disability & mortality - hypertension, which is another term for high blood pressure - coronary artery disease, which is a disease that involves restriction or blockages in the arteries that supply the heart with blood - cerebrovascular disease, which is a condition that affects the blood supply to the brain. - About 86 million Americans, more than 25% of the population, are living with some form of cardiovascular disease.

Modifiable risk factors for diabetes

- overweight and obesity - physical inactivity - smoking - alcohol consumptionq

"bad" cancers (based on 5-year survival rates)

- pancreas= 6% - liver= 14% - Esophagus= 17% - Lung&Bronchus= 16% - stomach= 26%

Cancer

- second leading cause of death in the US - characterized by uncontrolled cell proliferation - Although cancer is a disease that is often linked to the dangers of modern living and activities like drinking, smoking, and overeating, it has likely always been a part of the human condition. Today, cancer refers to a group of over 100 different diseases that are all characterized by features of abnormal cell growth and the potential for those aberrations in cell growth to spread to other areas of the body. Cancer begins with the development of a tumor, which is a region of excessive cell growth that forms a mass.

Predictive values are affected by the prevalence of disease in the population

- the predictive value of the test can change depending on the prevalence, even when the sensitivity and specificity remain constant. For positive predictive value, this is basically because the test is more likely to be accurate in terms of prediction when disease prevalence is high simply because a lot of people have the disease. - In other words, even if a test is returning positive results randomly—with no accuracy—positive predictive value would be higher in a highly diseased population because the test would just happen to be right more often due to the number of people who really are sick. Negative predictive value is affected by prevalence as well, just in the opposite direction (it becomes higher when prevalence is low). Because of these shortcomings of the predictive value, some researchers prefer to use what are known as likelihood ratios.

"good" cancers (based on 5-year survival rates)

- thyroid= 97% - testis= 95% - prostate= 99% - Melanoma= 91% - Breast= 89%

Time trends and epidemiology of diabetes

- type 2 represents 90-95% of cases - Type 1= 5-10% - The trend of increasing type 2 diabetes rates over time, however, is one of the more alarming statistics in epidemiology today. For example, take a look at the figure below showing the increase in the percentage and overall number of individuals in the U.S. population that have diagnosed diabetes from 1958 to 2009. - The increase in diabetes rates in the United States is also being seen throughout the world. In 1980, prevalence worldwide was around 4.7%. Now, it is approximately 8.5%. - Diabetes is the 7th leading cause of death in the United States, and 8th leading cause of death worldwide. Thus, the statistics concerning the increase in diabetes rates are concerning due not only to the rapidity in which they are rising, but also to the potential consequences for human health. The reasons for increasing diabetes rates are not fully understood, and researchers have implicated a variety of factors ranging from the widespread availability of cheap processed food to the recent evolutionary history of humankind, which made us very efficient at storing fat. There are likely multiple factors that have contributed to the trend.

___1______ is generally characterized by insulin deficiency, while______2____ is generally characterized by insulin resistance

1. type 1 diabetes 2. type 2 diabetes

Screening test

A test that is nonspecific and preliminary in nature; a way of detecting diseases in people who are sick but who arent displaying any symptoms= Asymptomatic or in incubation or latency period - Screening tests, therefore, target a population who are at risk for a particular disease. Most people who undergo a screening test will not be found to have a disease - Screening tests are generally not diagnostic tests, and individuals who are identified as potentially sick on a screening test must be referred for more specific diagnostic testing to confirm the screening test.

Atherosclerosis (Pathophysiology)

Atherosclerosis involves the build-up of substances found in the blood, like fat and cholesterol, in the walls of arteries until they form hardened structures called plaques. The plaques can increase in size until they begin to reduce the diameter of the inside of the artery, which makes it more difficult for blood to readily pass through. Sometimes plaques can grow so large they block arteries altogether. - Plaques in atherosclerosis (also known as atheromatous plaques) can also rupture, leading to the formation of blood clots within the artery. These clots form at the site of the plaque, in which case they are known as a thrombus, but they can also dislodge and travel to another location in the circulatory system, in which case they are known as an embolus. In either case, the blood clot itself can cause a blockage of an artery, restricting blood flow.

If a person does not have a disease, how often will the test be negative?

Example: a test with 90% specificity will correctly return a negative result for 90% of people who don't have the disease, but will return a positive result — a false-positive — for 10% of the people who don't have the disease and should have tested negative

In general, which of the following cancer stages has the worst prognosis?

IV

Infarction (Pathophysiology)

If the restriction continues for a prolonged period of time, the tissue will begin to die. The death of the tissue is referred to as infarction. - In a heart attack, ischemia causes the heart itself to be deprived of blood. This leads to death of the heart tissue, known as myocardial infarction. In a stroke, the brain is deprived of blood. In both of these outcomes, atherosclerosis is usually a preceding factor.

_________ specifically refers to a restriction in blood supply to a tissue

Ischemia

Biases in screening

Lead time bias= When attempting to compare survival time of patients who were screened vs. those who were not, lead time should always be excluded if possible. When included, it can make the screening method appear more effective at extending lifespan than it really is, and this is known as lead time bias. Length bias= Individuals with slower-progressing disease are more likely to have long incubation or latency periods than individuals with faster-progressing, more severe disease. Thus, individuals with slower-progressing disease are also those who are more likely to be detected through screening. Those with faster-progressing disease are more likely to already be displaying symptoms when someone with slower-progressing disease is identified as positive via screening. This makes screening appear more effective at extending lifespan, because it is identifying those who already have the best chance of surviving longer (due to the slower course of their disease). Overdiagnosis bias= occurs when screening identifies illness that likely would not have manifested into clinical (i.e. symptomatic) illness before a patient was afflicted or killed by some other disease. This often applies to older individuals, and once again it makes screening appear more effective than it really is because it is identifying cases of disease when treatment of that disease is unlikely to extend the person's lifespan.

Likelihood ratios

Likelihood ratios give us information about how confident we can be that a positive test actually represents someone with the disease or that a negative test actually represents someone without the disease. Unlike predictive values, likelihood ratios are not affected by prevalence. - Negative is odds of not having disease after negative test - Positive is odds of having disease following positive test

Patient #1 has a total cholesterol of 200 and HDL of 50. Patient #2 has a total cholesterol of 210 and HDL of 70. based on these numbers alone, which patient seems to have a higher risk of cardiovascular disease?

Patient #1

Negative is a proportion of people with negative tests who do not have disease

TN/(FN+TN) - You can see from this formula that negative predictive value represents the proportion of true negatives out of all the negative tests, as the combination of false negatives and true negatives in the denominator represents all the negative tests.

How to calculate specificity

TN/(TN+FP)

How to calculate sensitivity

TP/(TP+FN)

Positive is a proportion of people with positive tests who have disease

TP/(TP+FP) - You can see from this formula that positive predictive value represents the proportion of true positives out of all the positive tests, as the combination of true positives and false positives in the denominator represents all the positive tests.

role of insulin

The high blood glucose levels seen in diabetes are linked to a deficiency in the body's production of, or response to, the hormone insulin. Insulin is produced by the pancreas and its actions include prompting many cell types to take glucose up out of the blood. In patients with diabetes, there is either a deficiency in the pancreatic cells that produce insulin—causing insulin levels to be drastically reduced or non-existent—or the cells of the body have stopped responding adequately to insulin.

How to calculate and interpret TC:HDL ratios

There are two types of cholesterol-carrying molecules in the blood: low-density lipoproteins (LDLs) and high-density lipoproteins (HDLs). LDL particles seem to cause cholesterol to get stuck in atherosclerotic plaques, contributing to plaque formation. HDL particles, on the other hand, carry cholesterol away from the arteries and to the liver where it can be metabolized. Thus, higher levels of HDL particles decrease the risk of heart disease, while higher levels of LDL particles increase the risk. Because of this, a better estimate of risk than total cholesterol levels is a ratio of total cholesterol (TC) to HDL (TC:HDL). An ideal ratio is general considered to be 4:1 or less for men and 3.5:1 or less for women. For example, if a patient has a total cholesterol level of 180 and an HDL level of 60, his TC:HDL ratio would be 3:1. If another patient had a total cholesterol of 140 and an HDL of 30, his TC:HDL ratio would be 4.7. Thus, the second patient would be a greater risk of cardiovascular disease despite having a lower total cholesterol level.

secondary prevention

These individuals have not been diagnosed and have not yet begun receiving any treatment; thus screening is an attempt to detect disease early so treatment can begin as early as possible. Screening is also a type of

Ischemia (Pathophysiology)

When blood flow to a tissue is restricted, that tissue is deprived of oxygen and other important substances like glucose. This restriction is referred to as ischemia

Sensitivity (screening)

a measurement of how well a screening test identifies disease in individuals who really have the disease. It is the fraction of the diseased who test positive during the screening tool. sensitivity tells us how likely a person with the disease is to test positive. Formula: True positives/true positives+ false negatives

Tumor/neoplasm

any abnormal growth of cells - tumors may be benign or malignant

the diabetes prevention program found that

behavioral change can be more effective than metformin in reducing the risk of type 2 diabetes

individuals are classified as prediabetic based on their

blood glucose levels

Many of the major complications of diabetes are thought to start with the effect of hyperglycemia on

blood vessels

Embolus (Pathophysiology)

but they can also dislodge and travel to another location in the circulatory system, in which case they are known as an embolus

Diabetes

characterized by insulin deficiency or resistance

In the second have of the twentieth century, mortality rates due to cardiovascular disease have:

declined on average

A/an ___________ is a blood clot that is carried from its site of origin and can block a blood vessel at the site distant from its site of origin

embolus

Screening tests are generally used as diagnostic tests for individuals who were previously unaware they had the disease

false

The term "cancer" describes any tumor, whether the tumor is classified as benign or malignant

false

Despite the rapid increase in diabetes prevalence in the US, it is still not one of the top 10 causes of death

false number 7

An individual is screened for disease A and the screening test comes back positive. a subsequent diagnostic test finds they do not actually have the disease. the initial screening test is an example of a

false positive

hyperglycemia

high glucose levels in the blood

Diabetes mellitus was named based on what symptoms present in diabetics?

high urine output, high glucose levels in the urine

The most common form of cardiovascular disease is

hypertension

A screening tool helps lead to diagnosis of cancer 1 year earlier than the onset of clinical symptoms. however, this early diagnosis doesnt lead to an overall increase in longevity. if the 1 year difference in time of diagnosis is included in survival time when assessing the value of the screening tool, what type of bias is occurring

lead time bias

One reason to use likelihood ratios rather than predictive values is

likelihood ratios are not influenced by prevalence of the disease

which of the following types of cancer is responsible for causing the most cancer DEATHS in men and women

lung and bronchus

what are the most common causes of cancer deaths in males and females

lung cancer women- breast cancer men- prostate cancer

Specificity (screening)

measurement of how well a screening test identifies non-disease in individuals who do not have the disease. it is the fraction of the non-diseased who test negative using the screening tool. Specificity tells us how likely a person without the disease is to test negative formula: - true negatives/false positives+ true negatives

Predictive value

measurement of the screening tests actual ability to predict disease. - predictive value becomes a more useful tool clinically when explaining screening test results to someone, as it provides information on the proportion of individuals who test positive who have the disease and the proportion of individuals who test negative who do not. - Note the important distinction between sensitivity and specificity and predictive value: in the formula for sensitivity and specificity, the denominator is the individuals who have or do not have the disease, respectively. In the formula for predictive values, the denominator is the number of positive and negative tests. - Predictive values are popular ways of describing screening tests when clinicians are attempting to convey to patients what their test results mean. By saying, for example, that 99% of positive tests for a particular screening tool are true positives, the patient has a good appreciation for the likelihood of their actually having a disease after screening positive.

A new screening tool for a slowly-progressing disease is developed and is immediately used extensively, identifying a large number of disease cases. it is later learned, however, that many of the cases were identified at such a late stage that the patients were unlikely to have even experienced symptoms before dying of natural causes. this is an example of:

overdiagnosis bias

which of the following risk factors is present in up to 90% of type 2 diabetes causes

overweight and obesity

Insulin is produced primarily in the

pancreas

it is found that 90/100 of the positive tests for a particular screening tool were true positives. 90% is the:

positive predictive value

In a sample of 1000 people who are screened, 100 actually have disease A. the screening tool identifies 85/100 of the diseased individuals as potential disease cases. 85% is a measurement of the screening tools:

sensitivity

In a sample of 1000 people who are screened, 100 actually have disease B. A screening tool identifies 700 of the 900 non-diseased individuals as being disease-free. 78% (i.e. 700/900) is a measurement of the screening tools...

specificity

TN/(FP+TN)

specificity equation

Metastasis

spread of malignant cells - The ability to metastasize is what defines a malignant tumor, also known as cancer. In metastasis, cancer cells break away from the original, or primary, tumor, and spread through the bloodstream and lymphatic system to other locations in the body. Most of these cells are destroyed by the immune system, but some may find their way into other tissues where they can form secondary tumors.

which of the following cancers is generally considered to be "bad" based on 5-year survival rates?

stomach

A 5-year survival rate refers to

the proportion of patients who are still alive 5 years after cancer diagnosis

False negative

the screening test indicates a person is not sick. Further diagnostic testing determines they actually are sick.

True negative

the screening test indicates a person is not sick. Further diagnostic testing determines they are, indeed, not sick.

False positive

the screening test indicates a person is sick. Further diagnostic testing determines they are not sick.

True positive

the screening test indicates a person is sick. Further diagnostic testing determines they are, indeed, sick.

In assessing a screening test, a researcher calculates a likelihood positive likelihood ratio of 14. this suggests that

there is a very good chance that someone who receives a positive result on the test does actually have the disease

thrombus (Pathophysiology)

these clots form at the site of the plaque, in which case they are known as a thrombus

type 2 diabetes can be considered a pandemic

true

An individual is screened for disease A and the screening test comes back negative. A subsequent diagnostic test finds they do not actually have the disease. the initial screening test is an example of

true negative

Possible outcomes of screening tests

true positive, false positive, true negative, false negative -Obviously, an ideal screening test would only return true positives and true negatives. No screening test is perfect, however, and there will always be at least some incorrect results when examining a large group of screening test results

most of the diabetes cases in the world are of what type of diabetes

type 2

negative likelihood ratio

we create a ratio of the proportion of false negatives out of the diseased individuals to the proportion of true negatives among non-diseased individuals. The formula for negative likelihood ratio is: - false negatives/(true positives+false negatives)/true negatives/(false positives+true negatives)

positive likelihood ratio

we create a ratio of the proportion of true positives out of diseased individuals to the proportion of false positives among non-diseased individuals. The formula for the positive likelihood ratio is: true positives/(true positives+false negatives/false positives/(false positives+true negatives