Information

Standard Classification of Disease


I am working on a project for health center. It involves the creation of a database of all diseases. Currently I want to classify disease on the base of their category based on international standard.
Did anyone know where i can find one, I did a lot of research but was only able to come across this which seem not very useful to me: ICD


The two I know of off the top of my head are

  • OMIM : Online Mendelian Inheritance in Man. This is very good and very well organized but only deals with inheritable diseases, no infections etc.

  • Human disease ontology. From their webpage:

    The Disease Ontology has been developed as a standardized ontology for human disease with the purpose of providing the biomedical community with consistent, reusable and sustainable descriptions of human disease terms, phenotype characteristics and related medical vocabulary disease concepts through collaborative efforts of researchers at Northwestern University, Center for Genetic Medicine and the University of Maryland School of Medicine, Institute for Genome Sciences.

The DO is probably perfect for your needs.


I don't know if you're also interested in mental health issues, but the DSM (Diagnostic and Statistical Manual of Mental Disorders) is the standard typology for that subject area.

edit: I see that the Disease Ontology that @terdon lists also has mental health as a category.


International Classification of Diseases for Oncology, 3rd Edition (ICD-O-3)

Used principally in tumour or cancer registries for coding the site (topography) and the histology (morphology) of neoplasms, usually obtained from a pathology report.

Classification structure

A multi-axial classification of the site, morphology, behaviour, and grading of neoplasms.

The topography axis uses the ICD-10 classification of malignant neoplasms (except those categories which relate to secondary neoplasms and to specified morphological types of tumours) for all types of tumours, thereby providing greater site detail for non-malignant tumours than is provided in ICD-10. In contrast to ICD-10, the ICD-O includes topography for sites of haematopoietic and reticuloendothelial tumours.

The morphology axis provides five-digit codes ranging from M-8000/0 to M-9989/3. The first four digits indicate the specific histological term. The fifth digit after the slash (/) is the behaviour code, which indicates whether a tumour is malignant, benign, in situ, or uncertain (whether benign or malignant).

A separate one-digit code is also provided for histologic grading (differentiation).

Administrative status

Change description: Updates in nomenclature and Classification, with emphasis of changes on haematologic and neurologic neoplasms.

Reference documents

Available indexes:

A single combined alphabetical index for topography and morphology.

Available formats:

Training and training materials:

The European Network of Cancer Registries has provided training courses with the assistance of the International Agency for Research on Cancer, the European Commission and the United States National Cancer Institute

Languages

Published: Chinese, Czech, English, Finnish, Flemish/Dutch, French German, Japanese, Korean, Portuguese, Spanish, Romanian, Turkish

Relationships with other classifications

Correspondence between revisions

Correspondence tables are available between ICD-O revisions and between ICD-O revisions and ICD-9 and ICD-10.

Correspondence with international, multinational, national classifications

The topography classification is essentially that used by ICD-10 for malignant tumours.

Relationships &ndash conceptual, structural and other pertinent

Originally based on the American Cancer Society's Manual of Tumor Nomenclature and Coding (MOTNAC) first published in 1951.

Relationships with other terminologies

There is an agreement between the World Health Organization and the College of American Pathologists that the ICD-O morphology classification will be used for the M-8000 to M-9989 codes in the morphology axis of SNOMED. A change of SNOMED in 1993 led to incompatibilities for non-neoplastic lesions. For that reason ICD-O-3 does not longer include SNOMED codes for non-neoplastic lesions.

Steward/Custodian

The Secretariat / WHO
International Association of Cancer Registries
c/o International Agency for Research on Cancer

150, cours Albert Thomas
69372 Lyon Cedex 08
France

Contact information:

Mr Freddie Bray

International Agency for Research on Cancer
150, cours Albert Thomas
69372 Lyon Cedex 08
France
Telephone:(33) 4 72 73 80 56 Fax:Fax: (33) 4 72 73 86 96
E-mail: [email protected]

Dr Robert Jakob

World Health Organization
20 Av. Appia
1211 Geneva 27
Switzerland
E-mail: [email protected]


History of Pathology

Pathology has a history dating back to ancient times. The ancient Egyptians are one of the earliest known cultures to document disease and its effects on organs of the body. Ancient scrolls of papyrus contain information on bone injuries, parasites, and lumps that may have been cancer, among other diseases. Later on, starting in the 5th Century BC, the Greek physician Hippocrates had a profound influence on medicine and pathology. Many ancient Greek writers who were inspired by Hippocrates recorded detailed information on wounds, tumors, and diseases such as tuberculosis. Additionally, animal dissection began to be practiced. Hippocratic ideas then spread to Rome. During the Middle Ages, scientific progress slowed overall, but Byzantine and Arab physicians also made contributions to the study of disease.

The biggest revolution in pathology was the emergence of the microscope in the 19th Century. Now, for the first time, cells could be studied in detail. The focus of understanding disease changed from studying entire organs to focusing on individual cells. With the development and increased availability of microscopes, pathology research increased exponentially and led to huge scientific advancements such as organ and tissue transplants.


This image from the National Cancer Institute shows a pathologist and a surgeon examining cells under a microscope.


Like the classification systems for cellular organisms, virus classification is the subject of ongoing debate. This is largely due to the nature of viruses, which are not living organisms by the classic definition, but neither are they necessarily non-living. Therefore, viruses do not fit neatly into the biological classification system of cellular organisms, as plants and animals do.

Virus classification is based mainly on characteristics of the viral particles, including the capsid shape, the type of nucleic acid (DNA or RNA, double stranded (ds) or single stranded (ss)) within the capsid, the process of replication, their host organisms, or the type of disease they cause. The Table below lists characteristics such as capsid shape, presence of an envelope, and the diseases the viruses can cause.


Lesson 1: Introduction to Epidemiology

As with all scientific endeavors, the practice of epidemiology relies on a systematic approach. In very simple terms, the epidemiologist:

  • Counts cases or health events, and describes them in terms of time, place, and person
  • Divides the number of cases by an appropriate denominator to calculate rates and
  • Compares these rates over time or for different groups of people.

Before counting cases, however, the epidemiologist must decide what a case is. This is done by developing a case definition. Then, using this case definition, the epidemiologist finds and collects information about the case-patients. The epidemiologist then performs descriptive epidemiology by characterizing the cases collectively according to time, place, and person. To calculate the disease rate, the epidemiologist divides the number of cases by the size of the population. Finally, to determine whether this rate is greater than what one would normally expect, and if so to identify factors contributing to this increase, the epidemiologist compares the rate from this population to the rate in an appropriate comparison group, using analytic epidemiology techniques. These epidemiologic actions are described in more detail below. Subsequent tasks, such as reporting the results and recommending how they can be used for public health action, are just as important, but are beyond the scope of this lesson.

Defining a case

Before counting cases, the epidemiologist must decide what to count, that is, what to call a case. For that, the epidemiologist uses a case definition. A case definition is a set of standard criteria for classifying whether a person has a particular disease, syndrome, or other health condition. Some case definitions, particularly those used for national surveillance, have been developed and adopted as national standards that ensure comparability. Use of an agreed-upon standard case definition ensures that every case is equivalent, regardless of when or where it occurred, or who identified it. Furthermore, the number of cases or rate of disease identified in one time or place can be compared with the number or rate from another time or place. For example, with a standard case definition, health officials could compare the number of cases of listeriosis that occurred in Forsyth County, North Carolina in 2000 with the number that occurred there in 1999. Or they could compare the rate of listeriosis in Forsyth County in 2000 with the national rate in that same year. When everyone uses the same standard case definition and a difference is observed, the difference is likely to be real rather than the result of variation in how cases are classified.

To ensure that all health departments in the United States use the same case definitions for surveillance, the Council of State and Territorial Epidemiologists (CSTE), CDC, and other interested parties have adopted standard case definitions for the notifiable infectious diseases.(25) These definitions are revised as needed. In 1999, to address the need for common definitions and methods for state-level chronic disease surveillance, CSTE, the Association of State and Territorial Chronic Disease Program Directors, and CDC adopted standard definitions for 73 chronic disease indicators.(29)

Other case definitions, particularly those used in local outbreak investigations, are often tailored to the local situation. For example, a case definition developed for an outbreak of viral illness might require laboratory confirmation where such laboratory services are available, but likely would not if such services were not readily available.

Components of a case definition for outbreak investigations

A case definition consists of clinical criteria and, sometimes, limitations on time, place, and person. The clinical criteria usually include confirmatory laboratory tests, if available, or combinations of symptoms (subjective complaints), signs (objective physical findings), and other findings. Case definitions used during outbreak investigations are more likely to specify limits on time, place, and/or person than those used for surveillance. Contrast the case definition used for surveillance of listeriosis (see box below) with the case definition used during an investigation of a listeriosis outbreak in North Carolina in 2000.(25, 26)

Both the national surveillance case definition and the outbreak case definition require a clinically compatible illness and laboratory confirmation of Listeria monocytogenes from a normally sterile site, but the outbreak case definition adds restrictions on time and place, reflecting the scope of the outbreak.

Listeriosis &mdash Surveillance Case Definition

Infection caused by Listeria monocytogenes, which may produce any of several clinical syndromes, including stillbirth, listeriosis of the newborn, meningitis, bacteriemia, or localized infections

Laboratory criteria for diagnosis

Isolation of L. monocytogenes from a normally sterile site (e.g., blood or cerebrospinal fluid or, less commonly, joint, pleural, or pericardial fluid)

Confirmed: a clinically compatible case that is laboratory confirmed

Source: Centers for Disease Control and Prevention. Case definitions for infectious conditions under public health surveillance. MMWR Recommendations and Reports 1997:46(RR-10):49-50.

Listeriosis &mdash Outbreak Investigation

Clinically compatible illness with L. monocytogenes isolated

  • From a normally sterile site
  • In a resident of Winston-Salem, North Carolina
  • With onset between October 24, 2000 and January 4, 2001

Source: MacDonald P, Boggs J, Whitwam R, Beatty M, Hunter S, MacCormack N, et al. Listeria-associated birth complications linked with homemade Mexican-style cheese, North Carolina, October 2000 [abstract]. 50th Annual Epidemic Intelligence Service Conference 2001 Apr 23&ndash27 Atlanta, GA.

Many case definitions, such as that shown for listeriosis, require laboratory confirmation. This is not always necessary, however in fact, some diseases have no distinctive laboratory findings. Kawasaki syndrome, for example, is a childhood illness with fever and rash that has no known cause and no specifically distinctive laboratory findings. Notice that its case definition (see box below) is based on the presence of fever, at least four of five specified clinical findings, and the lack of a more reasonable explanation.

Kawasaki Syndrome &mdash Case Definition

A febrile illness of greater than or equal to 5 days&rsquo duration, with at least four of the five following physical findings and no other more reasonable explanation for the observed clinical findings:

  • Bilateral conjunctival injection
  • Oral changes (erythema of lips or oropharynx, strawberry tongue, or fissuring of the lips)
  • Peripheral extremity changes (edema, erythema, or generalized or periungual desquamation)
  • Rash
  • Cervical lymphadenopathy (at least one lymph node greater than or equal to 1.5 cm in diameter)

Laboratory criteria for diagnosis

Confirmed: a case that meets the clinical case definition

Comment: If fever disappears after intravenous gamma globulin therapy is started, fever may be of less than 5 days&rsquo duration, and the clinical case definition may still be met.

Source: Centers for Disease Control and Prevention. Case definitions for infectious conditions under public health surveillance. MMWR Recommendations and Reports 1990:39(RR-13):18.

Criteria in case definitions

A case definition may have several sets of criteria, depending on how certain the diagnosis is. For example, during an investigation of a possible case or outbreak of measles, a person with a fever and rash might be classified as having a suspected, probable, or confirmed case of measles, depending on what evidence of measles is present (see box below).

Measles (Rubeola) &mdash 1996 Case Definition

An illness characterized by all the following:

  • A generalized rash lasting greater than or equal to 3 days
  • A temperature greater than or equal to 101.0°F (greater than or equal to 38.3°C)
  • Cough, coryza, or conjunctivitis

Laboratory criteria for diagnosis

  • Positive serologic test for measles immunoglobulin M antibody, or
  • Significant rise in measles antibody level by any standard serologic assay, or
  • Isolation of measles virus from a clinical specimen

Comment: Confirmed cases should be reported to National Notifiable Diseases Surveillance System. An imported case has its source outside the country or state. Rash onset occurs within 18 days after entering the jurisdiction, and illness cannot be linked to local transmission. Imported cases should be classified as:

  • International. A case that is imported from another country
  • Out-of-State. A case that is imported from another state in the United States. The possibility that a patient was exposed within his or her state of residence should be excluded therefore, the patient either must have been out of state continuously for the entire period of possible exposure (at least 7-18 days before onset of rash) or have had one of the following types of exposure while out of state: a) face-to-face contact with a person who had either a probable or confirmed case or b) attendance in the same institution as a person who had a case of measles (e.g., in a school, classroom, or day care center).

An indigenous case is defined as a case of measles that is not imported. Cases that are linked to imported cases should be classified as indigenous if the exposure to the imported case occurred in the reporting state. Any case that cannot be proved to be imported should be classified as indigenous.

Source: Centers for Disease Control and Prevention. Case definitions for infectious conditions under public health surveillance. MMWR Recommendations and Reports 1997:46(RR-10):23&ndash24.

A case might be classified as suspected or probable while waiting for the laboratory results to become available. Once the laboratory provides the report, the case can be reclassified as either confirmed or &ldquonot a case,&rdquo depending on the laboratory results. In the midst of a large outbreak of a disease caused by a known agent, some cases may be permanently classified as suspected or probable because officials may feel that running laboratory tests on every patient with a consistent clinical picture and a history of exposure (e.g., chickenpox) is unnecessary and even wasteful. Case definitions should not rely on laboratory culture results alone, since organisms are sometimes present without causing disease.

Modifying case definitions

Case definitions can also change over time as more information is obtained. The first case definition for SARS, based on clinical symptoms and either contact with a case or travel to an area with SARS transmission, was published in CDC&rsquos Morbidity and Mortality Weekly Report (MMWR) on March 21, 2003 (see box below).(27) Two weeks later it was modified slightly. On March 29, after a novel coronavirus was determined to be the causative agent, an interim surveillance case definition was published that included laboratory criteria for evidence of infection with the SARS-associated coronavirus. By June, the case definition had changed several more times. In anticipation of a new wave of cases in 2004, a revised and much more complex case definition was published in December 2003.(28)

CDC Preliminary Case Definition for Severe Acute Respiratory Syndrome (SARS) &mdash March 21, 2003

Respiratory illness of unknown etiology with onset since February 1, 2003, and the following criteria:

  • Documented temperature > 100.4°F (>38.0°C)
  • One or more symptoms with respiratory illness (e.g., cough, shortness of breath, difficulty breathing, or radiographic findings of pneumonia or acute respiratory distress syndrome)
  • Close contact *within 10 days of onset of symptoms with a person under investigation for or suspected of having SARS or travel within 10 days of onset of symptoms to an area with documented transmission of SARS as defined by the World Health Organization (WHO)

* Defined as having cared for, having lived with, or having had direct contact with respiratory secretions and/or body fluids of a person suspected of having SARS.

Source: Centers for Disease Control and Prevention. Outbreak of severe acute respiratory syndrome&ndashworldwide, 2003. MMWR 2003:52:226&ndash8.

Variation in case definitions

Case definitions may also vary according to the purpose for classifying the occurrences of a disease. For example, health officials need to know as soon as possible if anyone has symptoms of plague or anthrax so that they can begin planning what actions to take. For such rare but potentially severe communicable diseases, for which it is important to identify every possible case, health officials use a sensitive case definition. A sensitive case definition is one that is broad or &ldquoloose,&rdquo in the hope of capturing most or all of the true cases. For example, the case definition for a suspected case of rubella (German measles) is &ldquoany generalized rash illness of acute onset.&rdquo (25) This definition is quite broad, and would include not only all cases of rubella, but also measles, chickenpox, and rashes due to other causes such as drug allergies. So while the advantage of a sensitive case definition is that it includes most or all of the true cases, the disadvantage is that it sometimes includes other illnesses as well.

On the other hand, an investigator studying the causes of a disease outbreak usually wants to be certain that any person included in a study really had the disease. That investigator will prefer a specific or &ldquostrict&rdquo case definition. For instance, in an outbreak of Salmonella Agona infection, the investigators would be more likely to identify the source of the infection if they included only persons who were confirmed to have been infected with that organism, rather than including anyone with acute diarrhea, because some persons may have had diarrhea from a different cause. In this setting, the only disadvantages of a strict case definition are the requirement that everyone with symptoms be tested and an underestimation of the total number of cases if some people with salmonellosis are not tested.

Exercise 1.4

Investigators of an outbreak of trichinosis used a case definition with the following categories:


Classification and Evolution

As you descend the taxonomic ranks from Domain à Species it becomes harder to distinguish and separate closely related organisms from each other and to place them accurately.

Reasons for the binomial naming system:

  • The same organism may have a completely different common name in different parts of a country
  • Different common names are used in different countries
  • Translation of languages and dialects may give different names
  • The same common name may be used for a different species in a different part of the world

Using observable features for classification

Species – a group of organisms that can freely interbreed to produce fertile offspring

This definition does not work for organisms that reproduce asexually and is very hard to apply to organisms known only from fossil records and the like.

Phylogenetic definition of species – a group of individual organisms that are very similar in appearance, anatomy, physiology, biochemistry and genetics

Early classification systems by Linnaeus and Aristotle were based solely on appearance and features which limited the classification to observable features only.

The Five Kingdoms

Evidence used in Classification

Some biological molecules, such as those for DNA replication and respiration are essential for life and therefore all living things have a variant that can be compared to show how closely related they are. If we assume that the earliest living common ancestors to living things had the same version of these molecules then any changes are a direct result of evolution.

The protein cytochrome C is essential in respiration but is not identical in all species due to evolution. The sequences of amino acids in the protein can help draw conclusions about how closely related they are. If the sequences are the same then the two species must be closely related and if they are different they are not so closely related. The more differences found between the sequences, the less closely related the two species.

RNA Polymerase is also used as an indicator of evolution because of its essential role in protein synthesis

Advances in genome sequencing have meant that the entire base sequence of an organism’s DNA can be determined. The DNA sequence of one organism can then be compared to the DNA sequence of another organism. This will show you how closely related they are to each other.

Proteins are made of amino acids. The sequence of amino acids in a protein is coded for by a base sequence in the DNA. Related organisms have similar DNA sequences and so similar amino acid sequences in their proteins.

3. Immunological Comparisons

Similar proteins will bind to the same antibodies. So, if antibodies to a human version of a protein were added to isolated samples from other species, then any protein similar to the human version will be recognised and bind to the antibody.

Artificial Classification – classification for convenience, e.g. in plant identification books, sorting by flower colour

Natural Classification – Biological classification involving a detailed study of the individuals in a species, it uses many characteristics, reflects evolutionary relationships and may change with advancing knowledge

Phylogeny– the study of the evolutionary relationships between organisms

Divergent evolution is where another species has evolved from the original common ancestor and the two species get progressively less similar.

Convergent evolution is where two species, who may share the same environment and therefore the same factors that affect survival, evolve similar characteristics.

Natural Selection

Natural Selection – the term used to explain how features of the environment apply a selective force on the reproduction of individual in a population

Charles Darwin did not invent the theory of evolution but he proposed natural selection as a mechanism towards the theory. It was controversial at the time as it countered the popular religious beliefs.

Darwin developed his ideas from the expedition he sailed with the HMS Beagle around the Galapagos Islands. Wallace was another naturalist who came to the same conclusion as Darwin.

  1. Offspring generally appear similar to their parents
  2. No two individuals are identical
  3. Organisms have the ability to produce large numbers of offspring
  4. Populations in nature tend to remain fairly stable in size
  5. There is a struggle to survive
  6. Better adapted individuals survive and pass on their characteristics
  7. Over time a number of changes may give rise to a new species

Fossil Evidence

In the past the world was inhabited by species that were different from those present today.

Old species have dies out and new species have arisen.

The new species that have appeared are often similar to the older ones found in the same place.

One of the most complete fossil records is that of the horse.

Variation – the presence of variety – the differences between individuals

Intraspecific variation – variation between members of the same species

Interspecific variation – the differences between species

Continuous variation – variation where there are two extremes and a full range of values in between

Discontinuous variation – variation where there are distinct categories and nothing in between

Causes of Variation

This includes the combination of alleles that is inherited from our parents which is completely unique to us (unless there is an identical twin).

Many characteristics are brought out by environmental changes. For example, an overfed pet can become obese and a person’s skin tone may change due to exposure to the sun.

Humans have become taller as the result of a better overall diet but however well your diet, you are unlikely to grow as tall as other people if your family is short.

Not all genes are active at any one time e.g. puberty is a time when many different genes are activating.

Changes in the environment can also directly affect which genes are active.

STATISTICS D:

  1. Sample a population – this has to be random
  1. Mean – to show variation between samples

3. Standard Deviation – to show the spread of values about the mean

4. Spearman’s Rank Correlation Coefficient – to consider the relationship of the data

5. Student’s t-test – used to compare two means

Adaptation – a characteristic that enhances survival in the habitat

Anatomical adaptations – structural features

Behavioural adaptations – the ways that behaviour is modified for survival

Physiological adaptations – affect the way that processes work (also called biochemical)

Marram Grass (example)

Natural Selection

  1. Mutation creates an alternative version of a gene (alleles)
  2. This creates genetic variation between the individuals of a species (intraspecific variation)
  3. When resources are scarce, the environment will select those variations (characteristics) that give an advantage. There is a selection pressure.
  4. Individuals with an advantageous characteristic will survive and reproduce
  5. Therefore they pass on their advantageous characteristics (inheritance)
  6. The next generation will have a higher proportion of individuals with the successful characteristics. Over time, the group of organisms becomes well adapted to their environment.

Pesticide Resistance in insects

An insecticide applies a very strong selection pressure. If the individual insect is susceptible then it will die, but if it has resistance it will survive and reproduce, spreading the resistance through the entire population.

e.g. Mosquitos have developed and enzyme that can break down the pyrethroids used to treat mosquito nets.

e.g. Insect populations have become resistant to the insecticide DDT which binds to a receptor on the plasma membrane of certain cells in insects. This is due to mutations in the genes coding for cell surface receptors.

When insects become resistant it leads to pesticides accumulating in the food chain. When predators eat the insect they may get a large dose of the insecticide. This is why DDT is banned in many areas.

Micro-organisms

The use of antibiotics is a strong selection pressure on bacteria. MRSA is a very resistant bacteria that has cropped up because of over prescription of antibiotics. Medical researchers are struggling to develop new and effective drugs as the bacterial populations rapidly become resistant to them.


Contents

It is necessary to distinguish between disease-related and drug-related biomarkers. Disease-related biomarkers give an indication of the probable effect of treatment on patient (risk indicator or predictive biomarkers), if a disease already exists (diagnostic biomarker), or how such a disease may develop in an individual case regardless of the type of treatment (prognostic biomarker). Predictive biomarkers help to assess the most likely response to a particular treatment type, while prognostic markers shows the progression of disease with or without treatment. [7] In contrast, drug-related biomarkers indicate whether a drug will be effective in a specific patient and how the patient’s body will process it.

In addition to long-known parameters, such as those included and objectively measured in a blood count, there are numerous novel biomarkers used in the various medical specialties. Currently, intensive work is taking place on the discovery and development of innovative and more effective biomarkers. These "new" biomarkers have become the basis for preventive medicine, meaning medicine that recognises diseases or the risk of disease early, and takes specific countermeasures to prevent the development of disease. Biomarkers are also seen as the key to personalised medicine, treatments individually tailored to specific patients for highly efficient intervention in disease processes. Often, such biomarkers indicate changes in metabolic processes.

The "classic" biomarker in medicine is a laboratory parameter that the doctor can use to help make decisions in making a diagnosis and selecting a course of treatment. For example, the detection of certain autoantibodies in patient blood is a reliable biomarker for autoimmune disease, and the detection of rheumatoid factors has been an important diagnostic marker for rheumatoid arthritis (RA) for over 50 years. [8] [9] For the diagnosis of this autoimmune disease the antibodies against the bodies own citrullinated proteins are of particular value. These ACPAs, (ACPA stands for Anti-citrullinated protein/peptide antibody) can be detected in the blood before the first symptoms of RA appear. They are thus highly valuable biomarkers for the early diagnosis of this autoimmune disease. [10] In addition, they indicate if the disease threatens to be severe with serious damage to the bones and joints, [11] [12] which is an important tool for the doctor when providing a diagnosis and developing a treatment plan.

There are also more and more indications that ACPAs can be very useful in monitoring the success of treatment for RA. [13] This would make possible the accurate use of modern treatments with biologicals. Physicians hope to soon be able to individually tailor rheumatoid arthritis treatments for each patient.

According to Häupl T. et al. prediction of response to treatment will become the most important aim of biomarker research in medicine. With the growing number of new biological agents, there is increasing pressure to identify molecular parameters such as ACPAs that will not only guide the therapeutic decision but also help to define the most important targets for which new biological agents should be tested in clinical studies. [14]

An NIH study group committed to the following definition in 1998: "a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention." In the past, biomarkers were primarily physiological indicators such as blood pressure or heart rate. More recently, biomarker is becoming a synonym for molecular biomarker, such as elevated prostate specific antigen as a molecular biomarker for prostate cancer, or using enzyme assays as liver function tests. There has recently been heightened interest in the relevance of biomarkers in oncology, including the role of KRAS in colorectal cancer and other EGFR-associated cancers. In patients whose tumors express the mutated KRAS gene, the KRAS protein, which forms part of the EGFR signaling pathway, is always ‘turned on’. This overactive EGFR signaling means that signaling continues downstream – even when the upstream signaling is blocked by an EGFR inhibitor, such as cetuximab (Erbitux) – and results in continued cancer cell growth and proliferation. Testing a tumor for its KRAS status (wild-type vs. mutant) helps to identify those patients who will benefit most from treatment with cetuximab.

Currently, effective treatment is available for only a small percentage of cancer patients. In addition, many cancer patients are diagnosed at a stage where the cancer has advanced too far to be treated. Biomarkers have the ability to greatly enhance cancer detection and the drug development process. In addition, biomarkers will enable physicians to develop individualized treatment plans for their cancer patients thus allowing doctors to tailor drugs specific to their patient's tumor type. By doing so, drug response rate will improve, drug toxicity will be limited and costs associated with testing various therapies and the ensuing treatment for side effects will decrease. [15]

Biomarkers also cover the use of molecular indicators of environmental exposure in epidemiologic studies such as human papilloma virus or certain markers of tobacco exposure such as 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK). To date no biomarkers have been established for head and neck cancer.

Once a proposed biomarker has been validated, it can be used to diagnose disease risk, presence of disease in an individual, or to tailor treatments for the disease in an individual (choices of drug treatment or administration regimes). In evaluating potential drug therapies, a biomarker may be used as a surrogate for a natural endpoint such as survival or irreversible morbidity. If a treatment alters the biomarker, which has a direct connection to improved health, the biomarker serves as a surrogate endpoint for evaluating clinical benefit. Some of the main areas in which molecular biomarkers are used in the drug development process are: early drug development studies, safety studies, proof of concept studies, and molecular profiling.

Molecular biomarkers are often used in early drug development studies. For instance, they are used in phase I study for establishing doses and dosing regimen for future phase II studies. PD biomarkers are commonly observed to respond (either decrease or increase) proportionally with dose. This data, in conjunction with safety data, help determine doses for phase II studies. In addition, Safety molecular biomarkers have been used for decades both in preclinical and clinical research. Since these tests have become mainstream tests, they have been fully automated for both animal and human testing. Among the most common safety tests are those of liver function (e.g., transaminases, bilirubin, alkaline phosphatase) and kidney function (e.g., serum creatinine, creatinine clearance, cystatin C). Others include markers of skeletal muscle (e.g., myoglobin) or cardiac muscle injury (e.g., CK-MB, troponin I or T), as well as bone biomarkers (e.g., bone-specific alkaline phosphatase).

For chronic diseases, whose treatment may require patients to take medications for years, accurate diagnosis is particularly important, especially when strong side effects are expected from the treatment. In these cases, biomarkers are becoming more and more important, because they can confirm a difficult diagnosis or even make it possible in the first place. [16] A number of diseases, such as Alzheimer's disease or rheumatoid arthritis, often begin with an early, symptom-free phase. In such symptom-free patients there may be more or less probability of actually developing symptoms. In these cases, biomarkers help to identify high-risk individuals reliably and in a timely manner so that they can either be treated before onset of the disease or as soon as possible thereafter. [17] [18]

In order to use a biomarker for diagnostics, the sample material must be as easy to obtain as possible. This may be a blood sample taken by a doctor, a urine or saliva sample, or a drop of blood like those diabetes patients extract from their own fingertips for regular blood-sugar monitoring.

For rapid initiation of treatment, the speed with which a result is obtained from the biomarker test is critical. A rapid test, which delivers a result after only a few minutes, is optimal. This makes it possible for the physician to discuss with the patient how to proceed and if necessary to start treatment immediately after the test.

Naturally, the detection method for a biomarker must be accurate and as easy to carry out as possible. The results from different laboratories may not differ significantly from each other, and the biomarker must naturally have proven its effectiveness for the diagnosis, prognosis, and risk assessment of the affected diseases in independent studies.

A biomarker for clinical use needs good sensitivity and specificity e.g. ≥0.9, and good specificity e.g. ≥0.9 [19] although they should be chosen with the population in mind so positive predictive value and negative predictive value are more relevant.

Biomarkers can be classified based on different criteria.

Based on their characteristics they can be classified as imaging biomarkers (CT, PET, MRI) or molecular biomarkers with three subtypes: volatile, like breath, [20] body fluid, or biopsy biomarkers.

Molecular biomarkers refer to non-imaging biomarkers that have biophysical properties, which allow their measurements in biological samples (e.g., plasma, serum, cerebrospinal fluid, bronchoalveolar lavage, biopsy) and include nucleic acids-based biomarkers such as gene mutations or polymorphisms and quantitative gene expression analysis, peptides, proteins, lipids metabolites, and other small molecules.

Biomarkers can also be classified based on their application such as diagnostic biomarkers (i.e., cardiac troponin for the diagnosis of myocardial infarction), staging of disease biomarkers (i.e., brain natriuretic peptide for congestive heart failure), disease prognosis biomarkers (cancer biomarkers), and biomarkers for monitoring the clinical response to an intervention (HbAlc for antidiabetic treatment). Another category of biomarkers includes those used in decision making in early drug development. For instance, pharmacodynamic (PD) biomarkers are markers of a certain pharmacological response, which are of special interest in dose optimization studies.

Types Edit

Biomarkers validated by genetic and molecular biology methods can be classified into three types. [21]

Molecular biomarkers have been defined as biomarkers that can be discovered using basic and acceptable platforms such as genomics and proteomics. Many genomic and proteomics techniques are available for biomarker discovery and a few techniques that are recently being used can be found on that page. Apart from genomics and proteomics platforms biomarker assay techniques, metabolomics, lipidomics, glycomics, and secretomics are the most commonly used as techniques in identification of biomarkers.

Many new biomarkers are being developed that involve imaging technology. Imaging biomarkers have many advantages. They are usually noninvasive, and they produce intuitive, multidimensional results. Yielding both qualitative and quantitative data, they are usually relatively comfortable for patients. When combined with other sources of information, they can be very useful to clinicians seeking to make a diagnosis.

Cardiac imaging is an active area of biomarker research. Coronary angiography, an invasive procedure requiring catheterization, has long been the gold standard for diagnosing arterial stenosis, but scientists and doctors hope to develop noninvasive techniques. Many believe that cardiac computed tomography (CT) has great potential in this area, but researchers are still attempting to overcome problems related to “calcium blooming,” a phenomenon in which calcium deposits interfere with image resolution. Other intravascular imaging techniques involving magnetic resonance imaging (MRI), optical coherence tomography (OCT), and near infrared spectroscopy are also being investigated.

Another new imaging biomarker involves radiolabeled fludeoxyglucose. Positron emission tomography (PET) can be used to measure where in the body cells take up glucose. By tracking glucose, doctors can find sites of inflammation because macrophages there take up glucose at high levels. Tumors also take up a lot of glucose, so the imaging strategy can be used to monitor them as well. Tracking radiolabeled glucose is a promising technique because it directly measures a step known to be crucial to inflammation and tumor growth.

Imaging disease biomarkers by magnetic resonance imaging (MRI) Edit

MRI has the advantages of having very high spatial resolution and is very adept at morphological imaging and functional imaging. MRI does have several disadvantages though. First, MRI has a sensitivity of around 10 −3 mol/L to 10 −5 mol/L which, compared to other types of imaging, can be very limiting. This problem stems from the fact that the difference between atoms in the high energy state and the low energy state is very small. For example, at 1.5 tesla, a typical field strength for clinical MRI, the difference between high and low energy states is approximately 9 molecules per 2 million. Improvements to increase MR sensitivity include increasing magnetic field strength, and hyperpolarization via optical pumping or dynamic nuclear polarization. There are also a variety of signal amplification schemes based on chemical exchange that increase sensitivity.

To achieve molecular imaging of disease biomarkers using MRI, targeted MRI contrast agents with high specificity and high relaxivity (sensitivity) are required. To date, many studies have been devoted to developing targeted-MRI contrast agents to achieve molecular imaging by MRI. Commonly, peptides, antibodies, or small ligands, and small protein domains, such as HER-2 affibodies, have been applied to achieve targeting. To enhance the sensitivity of the contrast agents, these targeting moieties are usually linked to high payload MRI contrast agents or MRI contrast agents with high relaxivities. [22]

Not all biomarkers should be used as surrogate endpoints to assess clinical outcomes. Biomarkers can be difficult to validate and require different levels of validation depending on their intended use. If a biomarker is to be used to measure the success of a therapeutic intervention, the biomarker should reflect a direct effect of that medicine.


Discussion

Users and Applications

Healthcare terminology and classification systems can be used by consumers, healthcare providers, quality and utilization management personnel, researchers, and other administrative staff (accounting, billing, and coding personnel). They are also used to facilitate communication between healthcare providers and consumers at the point of care for data collection purposes. A more organized system of data collection and retrieval can be provided by utilizing healthcare terminology. This system can promote quality of care by providing a link between published research and clinical care. Furthermore, such systems can support integration of care by allowing effective exchange of clinical information among healthcare providers in different settings. Although terminologies such as SNOMED CT can be utilized to support real-time decision making and retrospective reporting for research and management, such utilization can hindered by complexity of these systems. Classification systems are utilized by wider spectrum of users in healthcare. They can be used to provide data to consumers on costs, treatment options, and outcomes. Also, classification systems provide a less complex system for data collection and reporting that can be further used for research purposes. Information provided by such systems can be used to improve clinical, financial, and administrative performance by enabling effective payment systems, identifying potential fraud and abuse, and ensuring accurate reporting.

ICD-10-CM/PCS

The ICD coding system was originally created to code death certificates, but its use has expanded to encompass a wide range of statistical reporting. In fact, ICD-10 has been used since the 1990s to collect mortality statistics around the globe. The WHO defines coding as “the translation of diagnoses, procedures, co-morbidities and complications that occur over the course of a patient’s encounter from medical terminology to an internationally coded syntax.” 85 In this definition, the WHO acknowledges the capability of the ICD system that is used for clinical coding and classification to enable international comparisons with respect to mortality as well as morbidity statistics.

ICD-9-CM had been used since 1978 as the foundation of the reimbursement system in the United States and is used by the Center for Medicare and Medicaid Services for inpatient and ambulatory resource grouping. The Medicare Severity Diagnosis Related Group (MS-DRG) system constitutes the foundation of Medicare’s Inpatient Prospective Payment System (IPPS), which is used to reimburse acute-care and short-term hospitals for services rendered to Medicare beneficiaries. ICD-9-CM was replaced by ICD-10-CM/PCS in October 1, 2015, and it will continue to serve as a base for healthcare reimbursement. For outpatient encounters, reporting of diagnosis codes in ICD-10-CM is required to establish medical necessity.

Also, ICD-10-CM is now used in place of ICD-9-CM for public health reporting (i.e., reporting the leading cause of death and morbidity on the national level). ICD-10-CM/PCS can also be used to assess clinical outcomes and improve quality of care provided for individual patients. For example, ICD-10-CM/PCS data are utilized for clinical documentation improvement initiatives to educate physicians on effective clinical documentation in EHR systems.

However, the process of clinical classification itself is prone to variation because of the complex coding schemes and conventions that are subjected to interpretation by coders, which makes it difficult for clinicians to assign the codes by themselves. Thus, ICD-10 in general and ICD-10-CM/PCS in particular lacks the standardization needed for electronic communication and clinical documentation.

SNOMED CT

SNOMED CT provides a unified language that can be used as a standard for communication among healthcare providers and across clinical applications. SNOMED CT can contribute greatly to semantic interoperability in healthcare applications. 86–88 Its standardized logical structure as well as its wide acceptance makes it more suitable than other terminologies or classification systems for high-level information sharing and information retrieval. 89–91 Thus, SNOMED CT can be used for health information exchange and clinical documentation in EHRs. SNOMED CT is an automated system, which makes it convenient to be used at the point of care for generating clinical alerts and reminders, serve as a part of a clinical decision-support system, and link providers to medical knowledge and current publications that can be used for outcome measurement. Furthermore, because of its fully automated scheme, SNOMED CT can be used for healthcare research, and it can be used for automated identification of patients for clinical trials because of its extensive granularity and content coverage. 92–96 In addition to its higher specificity, SNOMED CT has a unique feature that enables extension of concepts by end users, which can foster reliable communication among healthcare providers and across medical specialties and can facilitate health information exchange at national as well as international levels. 97 SNOMED CT has become one of the federal requirements for health information technology CMS mandates the use of SNOMED CT to code the problem list for Meaningful Use stage 2. 98, 99

Clinical Documentation in the EHR

However, the information provided above should not be take to suggest that SNOMED CT is superior to ICD-10-CM/PCS, as both coding schemes provide the necessary data structure needed to support healthcare clinical and administrative processes. Clinical terminology systems as well as clinical classification systems were originally designed to serve different purposes and different users’ requirements. ICD-10-CM/PCS is an output system that was designed for general reporting purposes, public health surveillance, administrative performance monitoring, and reimbursement of healthcare services. In contrast, SNOMED CT was developed to serve as a standard data infrastructure for clinical application, which requires a greater degree of specificity. A classification system can be less detailed than a clinical terminology. 100 Therefore, the lower specificity of ICD-10-CM/PCS is an intrinsic feature rather than a shortcoming SNOMED CT is too detailed to replace ICD-10-CM/PCS in this context. In fact, the systems complement each other and contribute to providing quality data for different domains of the healthcare system. For example, “If a researcher wants to know how many patients died with a diagnosis of heart attack last year, ICD-10 (WHO’s) is enough. If they want more detail, such as what muscle of the heart was involved, they will need SNOMED CT.” 101 Therefore, both systems can be used in research and education depending on which degree of specificity is required by circumstances: SNOMED is a better choice for identifying rare diseases, while ICD-10-CM/PCS is more efficient for general reporting, such as collecting the top causes of mortality and morbidity at the national level. Furthermore, ICD-10-CM/PCS will be needed to constitute the foundation of reimbursement in the United States. 102

Mapping SNOMED CT to ICD-10-CM/PCS

The NLM, with participation of the National Center for Health Statistics, is working on a project to map SNOMED CT concepts to ICD-10-CM codes, called I-MAGIC (Interactive Map-Assisted Generation of ICD Codes). According to NLM, the purpose of mapping is to “is to support semi-automated generation of ICD-10-CM codes from clinical data encoded in SNOMED CT” 103 in order to fulfill the requirements of healthcare. Therefore, SNOMED CT cannot replace ICD-10-CM/PCS both systems complement each other and equally contribute to quality data structure for the entire healthcare system. In fact, the WHO, together with the IHTSDO, has been working on similar projects that will enable mapping between SNOMED CT and ICD-10 (the WHO version) as well as ICD-11. However, because of the substantial differences between these coding schemes, it is not always possible to have one-to-one mapping. However, these mapping projects further emphasize the importance of future data infrastructure that encompasses characteristics of both systems to achieve the maximum benefits of information technology in healthcare.


Resource text

International classifications

The international standard classification of disease is the International Classification of Diseases (ICD), published by the World Health Organisation. It is periodically updated the current version is ICD-10, which was implemented in 1994, and is beginning to show its age. The ICD is divided into a series of chapters, such as II, neoplasms, or IV, Endocrine, nutritional and metabolic diseases. In the 10th revision, each individual disease is given a unique alpha numeric code. For example, cancer of the stomach is C16, which can be subdivided more precisely (C16.2 is cancer of the body of the stomach).

ICD is used to classify diseases and other health problems recorded on many types of health and vital records, including death certificates and hospital records. In addition to enabling the storage and retrieval of diagnostic information for clinical and epidemiological purposes, these records also provide the basis for the compilation of national mortality and morbidity statistics by WHO Member States. In the UK it is used within the NHS when capturing diagnosis information in hospitals, and is an important part of the identification of Healthcare Related Groups (HRGs), used for resource management and payment of providers.

Another method of classification is the American Psychiatric Association's (APA) Diagnostic and Statistical Manual of Mental Disorders (DSM), which is the primary diagnostic system for psychiatric and psychological disorders within the United States, and is used as an adjunct diagnostic system in many other countries. Since the 1990s, the APA and WHO have worked to bring the DSM and the relevant sections of ICD into concordance, but some small differences remain.

The International Classification of Functioning, Disability and Health (ICF) describes health and health-related domains as body functions and structures, activities and participation. Because an individual's functioning and disability occur in a context, ICF includes a list of physical, social, attitudinal and environmental factors. Domains are classified by body, individual and societal perspectives. The classification places emphasis on function rather than condition or disease. It is designed to be applicable across cultures, age groups and gender, making ICF the basis for collecting reliable and comparable data on health outcomes for individuals and populations.

The World Health Assembly approved ICF in May 2001 after a decade-long international revision process involving 65 different countries. ICF is designed for better, more uniform data for research and analysis. It will eventually be implemented worldwide, meaning that health and disability can be described and measured more effectively, and that the impact of these conditions can be monitored.

Datasets that utilise international classification systems enable comparability across countries in the collection, processing, classification, and presentation of these statistics. However, new or emerging diseases are not easily included without a major revision. Each revision may lead to problems interpreting trend data.

Classifications used in the NHS

There are three types of classification which may be relevant for data collection and analysis. These are Read Codes, PPCS 4 code, and healthcare resource groups (HRGs).

Read codes, or Clinical Terms, were developed initially for use in primary care. They have a hierarchical structure describing the care and treatment of patients, including diagnosis, symptoms, tests and other interventions, and can (mostly) be mapped to ICD10 and OPCS4. However, they have not generally been found easily usable at hospital levels, they are not always unique for a particular presenting condition (depending on the hierarchical sequence followed to arrive at the final code), and their ethnic categories do not correspond with those used elsewhere. Though they formed a major plank of an earlier NHS Information Strategy, they have not taken the place they were expected to.

SNOMED (Systematic Nomenclature of Medicine) is similar to Read Codes but is more widely used in the US. A major project to combine SNOMED with the UK Read codes to form SNOMED-CT has not proved as successful as anticipated.

The Office of Populations, Census and Surveys (as it formerly was, before becoming part of the Office of National Statistics) produced classifications of operative interventions known as OPCS 4. Within the UK these are standard codes used in hospital datasets to record surgical interventions. Along with ICD10 codes, they are used to derive HRG codes. The most recent release is OPCS4, which dates from the 1980s and is recognised as in need of revision. However, there has as yet been no consensus as to the best form of replacement. SNOMED-CT was expected to do this, however this has not taken place to date.

The third type of classification is an NHS development of the US system of Diagnostic Related Groups (DRGs). DRGs are used for payment of hospitals by health insurance organisations, and HRGs are used by the NHS to set standard reimbursements for care carried out. HRGs are intended to group cases of similar clinical character and similar resource use, and as such can be a valuable tool for healthcare analysts concerned with appropriate targeting and utilisation of NHS resources. They are regularly reviewed and updated, and are currently (2007-8) at version 4. For more information, see the Information Centre: Casemix.


2018 AHA/ACC Guideline for Adults With Congenital Heart Disease

The following are key points to remember from the 2018 American Heart Association/American College of Cardiology (AHA/ACC) Guideline for the Management of Adults With Congenital Heart Disease (ACHD):

  1. This guideline is a major update to the ACC/AHA 2008 guidelines for the management of ACHD. The 2018 guideline reflects the new format of presenting guidelines, including tables of related recommendations, a brief synopsis, recommendation-specific supportive text, and flow diagrams. This review will emphasize areas of difference between the new and the previous guidelines as well as lesion-specific recommendations considered to be of interest to practitioners.
  2. The guideline development process prompted the commissioning of two independent evidence review committees (ERCs) to address two significant clinical questions. The first ERC addressed the issue of the benefit of intervention for asymptomatic patients with secundum atrial septal defects (ASDs) and right ventricular (RV) dilatation. The second ERC addressed the issue of the role of medical therapy, including angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, beta-blockers, and aldosterone antagonists in adults with systemic right ventricles.
  3. The guideline presents a new classification system for ACHD. The adult congenital heart disease anatomic and physiological (ACHD AP) classification system uses both anatomic complexity and as well as physiologic status. Anatomic classification includes Class I (simple), Class II (moderate complexity), and Class III (great complexity). The physiological classification is divided into stages A-D and is overall similar to the AHA heart failure classification. The physiological classification system takes into account a patient’s functional status as well as other factors including presence of valve disease, pulmonary hypertension, arrhythmias, aortic dilatation, end-organ function, and cyanosis.
  4. The need for such a classification system is based on data that allow better refinement of patient classification that uses physiologic variables in addition to anatomic categorization. For example, a patient with repaired tetralogy of Fallot with no significant pulmonary regurgitation, no symptoms, and no other sequelae would be ACHD AP classification IIA, whereas another patient with tetralogy of Fallot but with severe pulmonary valve regurgitation and exercise intolerance would be ACHD AP classification IIC. This distinction allows patients to be followed prospectively in a fashion more reflective of the interplay between their congenital abnormality and physiologic impact.
  5. The ACHD AP classification system provides the basis for making lesion-specific recommendations regarding interval of clinical follow-up and testing modalities such as electrocardiograms, transthoracic echocardiography, cardiovascular magnetic resonance, and exercise testing.
  6. Two recommendations related to closure of secundum ASD were informed by a systemic review. In adults with secundum ASD and impaired functional capacity, right atrial and/or RV enlargement, Qp:Qs ≥1.5:1, and absence of cyanosis at rest or during exercise, device or surgical closure is recommended if systolic pulmonary artery pressure is 2 , RV end-systolic volume index ≥80 ml/m 2 ), RV end-diastolic volume ≥2x LV end-diastolic volume, RV systolic pressure ≥2/3 systemic pressure, and/or progressive reduction in objective exercise capacity.
  7. Primary prevention implantable cardioverter-defibrillator therapy is reasonable in adults with tetralogy of Fallot and multiple risk factors for sudden cardiac death (SCD) (COR IIa, LOE B-NR). Risk factors for SCD include LV systolic or diastolic dysfunction, nonsustained ventricular tachycardia, QRS duration ≥180 ms, extensive RV scarring, and inducible sustained ventricular tachycardia at electrophysiological study.
  8. The systemic review conducted regarding impact of medical therapy in patients with systemic right ventricles demonstrated that medical therapy for systolic ventricular dysfunction remains largely uncertain. As a result, no recommendations regarding medical therapy for systolic dysfunction of systemic right ventricles were made.
  9. It is reasonable to perform anatomic evaluation of coronary artery patency, i.e., catheter angiography or CT or MR angiography in asymptomatic adults with dextro-transposition of the great arteries (d-TGA) with arterial switch (COR IIa, LOE B-NR). Physiologic tests of myocardial perfusion for adults with d-TGA after arterial switch can be beneficial for assessing symptoms of myocardial ischemia (COR IIa, LOE C-EO).
  10. Pulmonary vasoactive medications can be beneficial to improve exercise capacity in adults with Fontan repair (COR IIa, LOE B-R).
  11. At the conclusion of the document, the writing committee describes evidence gaps in the management of ACHD and proposes future directions to address these issues.

Keywords: Aortic Coarctation, Aortic Diseases, Arrhythmias, Cardiac, Cardiac Catheterization, Cardiac Imaging Techniques, Cardiovascular Surgical Procedures, Cyanosis, Death, Sudden, Cardiac, Defibrillators, Implantable, Delivery of Health Care, Delivery of Health Care, Integrated, Diagnostic Imaging, Dilatation, Echocardiography, Electrocardiography, Endocarditis, Exercise, Exercise Test, Functional Residual Capacity, Genetic Diseases, Inborn, Heart Defects, Congenital, Heart Failure, Heart Septal Defects, Atrial, Heart Transplantation, Heart Valve Diseases, Hypertension, Pulmonary, Motor Activity, Myocardial Ischemia, Organization and Administration, Palliative Care, Patient Care Team, Pregnancy, Primary Prevention, Sports Nutritional Sciences, Surgical Procedures, Operative, Tachycardia, Ventricular, Tetralogy of Fallot