Purpose of investigation: Difference between revisions

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When one orders a test (laboratory, imaging, or otherwise), it's important to have a predetermined purpose for the test and not just ordering tests willy-nilly. Generally, investigations can be used for:
When one orders a test (laboratory, imaging, or otherwise), it's important to have a predetermined purpose for the test and not just ordering tests willy-nilly. Tests are often invasive as well as time-consuming and expensive, and so they should be worth the risk, time, and expense. There is no point in ordering a test if the test result does not influence how you approach the patient.


* Screening (healthy or not healthy)
Generally, investigations can be used for:
* Lab diagnosis
 
* [[Screening]]
* Diagnosis
* Follow-up/monitoring
* Follow-up/monitoring
** Monitoring progression/response to treatment
** Monitoring progression/response to treatment
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** Information regarding the likely outcome of the disease
** Information regarding the likely outcome of the disease


== Features of investigations ==
== Value to the patient ==
Any single test or investigation has a certain features which are important to know about, like sensitivity.
An investigation should have some form of value for the patient (except if done in a research setting or for epidemiological purpose, in which case the investigation has value for researchers, and in turn, future patients). The value to the patient should also weigh up for any negative consequences of the investigation.


=== True and false positive and negative ===
=== Frail patients ===
When researching a certain test's characteristics and usefulness in diagnosing a certain disorder, one would perform the test on both healthy people and people with the disorder. A good test will be positive in most people with the disorder and negative in most people without the disorder. However, because no test is perfect, the test will be negative in some people with the disorder, and it will be positive in some people without the disorder.
Many frail patients, especially elderly, cannot or do not want to undergo certain tests or invasive procedures. Is there, for example, a point in evaluating a frail elderly person for cancer, if they do not want to or cannot undergo cancer treatment anyway? Take the following example:


After performing the test on a number of subjects, each subject will be put into one category:
A frail elderly patient living in an institution (like a nursing home) has a positive [[faecal occult blood test]]. The physician considers to refer them to [[colonoscopy]], but stops to consider: how will a colonoscopy be of value to the patient? In their current state, even if the colonoscopy would show [[colorectal cancer]], the patient would not be a candidate for any surgery or chemotherapy, so even if a diagnosis is made, nothing will change for the patient (except the stress of knowing they have cancer). In addition, colonoscopy is an invasive investigation which requires strict patient preparation, which can be difficult for a frail elderly to perform or even survive.


* True positives (TP) - those who have the disorder and tested positive with the test
If they have colorectal cancer and it grows and eventually causes [[intestinal obstruction]], colonoscopy may be indicated for stenting the bowel, in which case the colonoscopy would have value for the patient as [[palliative therapy]]. As such, one could note that the patient may have colorectal cancer, and only refer them to colonoscopy if intestinal obstruction is suspected at a later time.
* False positives (FP) - those without the disorder but who tested positive anyway
* True negatives (TN) - those without the disorder and who tested negative
* False negatives (FN) - those with the disorder but who tested negative anyway


The best tests have as few false positives and false negatives as possible.
One can also argue that even performing a faecal occult blood test in this case has no value for the patient, because the next step after a positive test would be a colonoscopy, a procedure which would not be of value to the patient anyway.


=== Sensitivity ===
=== Patient management is the same regardless of test result ===
For a given test and illness, sensitivity refers to the proportion of sick people who are tested that produce a positive test result. In terms of the above, in a certain population, sensitivity refers to the ratio of how many people are True Positives of those who have the disorder (True Positives + False Negatives).
In some cases, it may be temping to order an investigation to gain more information, but it's important to consider whether that information is of value or not. Take the following example:


A perfectly sensitive test is 100% sensitive, meaning that 100% of tested sick people will test positive, meaning that no sick people will test negative. Few tests are 100% sensitive, and in real-life, most test which are regarded as highly sensitive have sensitivities around 95%.
A young male has had lower back pain for a few days. The pain is not severe, and there are no red flags for [[cauda equina syndrome]]. He wants an [[MRI]] to know what's going on, but the physician stops to consider: how will an MRI be of value to the patient? The patient may or may not have a [[herniated disc]], but even if they do, a herniated disc without red flags isn't an indication for surgery anyway. As such, whether the MRI shows a herniated disc or not, the management will be the same (no surgery, only physical therapy and pain relief), and the MRI is therefore of no value to the patient (and it is resource-intensive).


An example of a highly sensitive test is measuring [[D-dimer]] in suspected [[venous thromboembolism]], which has a sensitivity of 95%.
On the other hand, if the patient has debilitating pain or there are red flags present, he may have cauda equina syndrome, in which case surgery is indicated. In this case, MRI has value: it determines whether they need surgery or not.


An example of a test which is less sensitive is [[chest radiography]] in suspected [[lung cancer]], which has a sensitivity of approximately 90%.
Another example:


The sensitivity of a test is not affected by the prevalence of the disease in the tested population.
A middle aged woman has symptoms of an [[upper respiratory tract infection]]. After taking the anamnesis and physical examination, you're certain that it's a viral infection. You reflexively want to order a [[CRP]] or [[leukocyte count]], but you stop to consider: will the laboratory investigation likely be of value to the patient? You know that viral URTIs only cause mildly elevated inflammatory parametres, so that's likely what you'll find anyway. And even if the CRP is higher than you expect, you're certain enough that this is not a bacterial infection, so you won't be administering antibiotics anyway. So even after making the investigation, you'll most likely not be changing your management of this patient; managing their symptoms and encouraging rest, without antibiotics.


=== Specificity ===
On the other hand, if the patient has symptoms which make it difficult to distinguish between viral and bacterial infection clinically, a laboratory investingation is merited, as it provides additional information which can aid in the diagnosis and therefore the treatment in this case.
For a given test and illness, specificity refers to the proportion of healthy people who are tested that produce a negative test result. In terms of the above, in a certain population, specificity refers to the ratio of how many people are True Negatives of those who do not have the disorder (True Negatives + False Positives).  


A perfectly specific test is 100% specific, meaning that 100% of tested healthy people will test negative, meaning that no healthy people will test positive. Few tests are 100% specific, and in real-life, most test which are regarded as highly specific have specificities around 95%.
Consider that many laboratories can analyse a pharyngeal swab for specific airway viruses. Would making such an investigation in this case change the management of the patient? In most cases no, as there is no specific treatment for most airway viruses anyway.
 
== Diagnosis ==
An example of a highly specific test is measuring [[Anti-tissue glutaminase antibody|anti-tissue glutaminase antibodies]] in suspected [[coeliac disease]], which has a specificity of 95%.
When an investigation is ordered for diagnosis, one should already have a list of differential diagnoses before ordering the test, and the test should be able to narrow down the list of differential diagnoses. It's important to consider the test's [[specificity]], [[sensitivity]], [[positive predictive value]], and [[negative predictive value]] in this. There is no reason to perform an investigation if it doesn't help narrow down the number of differential diagnoses or doesn't validate your tentative diagnosis.  
 
An example of a test with low specificity is measuring [[PSA]] in suspected [[prostate cancer]], which has a specificity of 20%.
 
The specificity of a test is not affected by the prevalence of the disease in the tested population.
 
Unfortunately, when designing a test, there is most commonly a tradeoff between sensitivity and specificity. One cannot design a test to be perfectly sensitive, as that would produce many false positives, as such giving a low specificity, and vice-versa.
 
=== Pre-test and post-test probability ===
The pre-test probability refers to the probability that a patient with a certain symptom or clinical finding has a certain condition ''before'' performing a test or investigation. For an asymptomatic person, the pre-test probability is equal to the prevalence of the disease in the general population. For a symptomatic person, the pre-test probability is equal to the prevalence in a population of people with the condition ''and'' the previously mentioned symptom. As such, if the patient has symptoms or clinical findings, they have a higher probability of having the disease than the general population, and so the pre-test probability is higher than the prevalence.
 
As an example, the prevalence of [[urinary tract infection]] in the general population is 11%, meaning that, if you pick a random person in the world, there is an 11% chance that they have an UTI, regardless of whether they have symptoms. However, among all people with typical urinary tract infection symptoms, approximately 80% of them have urinary tract infection. As such, if a person has typical urinary tract infection symptoms, the pre-test probability of them having UTI is 80%.
 
Likewise, the post-test probability refers to the probability that a patient with a certain symptom or clinical finding has a certain condition ''after'' performing the test or investigation. Ideally, a test should increase the post-test probability to be much higher than the pre-test probability.
 
=== Positive predictive value ===
For a given test and illness, the positive predictive value (PPV) of a test refers to the probability that a patient has the illness if they have tested positive. Intuitively, it can be difficult to understand the difference between specificity and PPV, and I've given up trying to understand why. However, it's only important to know that the positive predictive value of a test is perhaps more important for us than sensitivity, as it tells us more about the usefulness of a test than the test's sensitivity.
 
In a certain population, positive predictive value refers to the ratio of how many people are True Positives of those who tested positive (True Positives + False Positives).
 
In many cases, test with high specificity have high positive predictive value as well. I can't think of any specific examples.
 
However, and this is important to know, the positive predictive value of a test depends not only on the test's characteristics but also the pre-test probability of the disorder, which in turn is equal to the prevalence of the disorder (if there are no symptoms). When the pre-test probability increases, the PPV increases as well, and vice-versa. As such, even if the test is excellent and has a high specificity and sensitivity, the test may have a low positive predictive value regardless if the prevalence is low (the disease is rare).
 
=== Negative predictive value ===
For a given test and illness, the negative predictive value (NPV) of a test refers to the probability that a patient does not have the illness if they have tested negative. Like positive predictive value, the negative predictive value is important as it tells us the probability that the patient does not have the disease if they test negative.
 
In a certain population, negative predictive value refers to the ratio of how many people are True Negatives of those who tested negative (True Negatives + False Negatives).
 
In many cases, tests with high sensitivity have high negative predictive value as well. For example, unless the pre-test probability is high, a negative D-dimer has a close to 100% negative predictive value for venous thromboembolism. As such, patients with a low or medium pre-test probability for VTE who test negative for D-dimer have VTE ruled out.
 
As with PPV, the negative predictive value of a test depends not only on the test's characteristics but also the pre-test probability of the disorder. However, in contrast to PPV, NPV ''decreases'' as the prevalence increases. As such, even if the test is really accurate and has a high specificity and sensitivity, the test may have a low negative predictive value regardless if the prevalence is high (the disease is common).
 
== Value to the patient ==
An investigation should have some form of value for the patient (except if done in a research setting or for epidemiological purpose, in which case the investigation has value for researchers, and in turn, future patients). The value to the patient should also weigh up for any negative consequences of the investigation.


Common examples to consider:
This article leans heavily on statistical terms like probability and thresholds. In real-life, the exact probability and thresholds cannot be known in most circumstances. Instead, we think of these factors in approximate terms based not on statistical analysis but our own experience and knowledge. 


* A frail elderly patient living in an institution (like a nursing home) has a positive faecal occult blood test. The physician considers to refer them to colonoscopy, but stops to consider: how will a colonoscopy be of value to the patient? In their current state, even if the colonoscopy would show colorectal cancer, the patient would not be a candidate for any anticancer surgery or chemotherapy, so even if a diagnosis is made, nothing will change for the patient (except the stress of knowing they have cancer). In addition, colonoscopy is an invasive investigation which requires strict patient preparation, which can be difficult for a frail elderly to perform or even survive.
=== Approach to diagnosis ===
** If they have colorectal cancer and it grows and eventually causes intestinal obstruction, colonoscopy may be indicated for stenting the bowel, in which case the colonoscopy would have value for the patient as palliative therapy
When a patient is presented with symptoms or clinical findings, one should formulate a list of differential diagnoses which could be underlying. Often, this is not a conscious process but rather an unconscious one.
** One can also argue that even performing a faecal occult blood test in this case has no value for the patient, because the next step after a positive test would be a colonoscopy, a procedure which would not be of value to the patient anyway
* A young male has had back pain for a few days. The pain is not severe, and there are no red flags for cauda equina syndrome. He wants an MRI to know what's going on, but the physician stops to consider: how will an MRI be of value to the patient? The patient may or may not have a herniated disc, but even if they do, a herniated disk without red flags isn't an indication for surgery anyway. As such, whether the MRI shows a herniated disc or not, the management will be the same (no surgery, only physical therapy and pain relief), and the MRI is therefore of no value to the patient (and it is resource-intensive)
** On the other hand, if the patient has debilitating pain or there are red flags present, he may have cauda equina syndrome, in which case surgery is indicated. In this case, MRI has value: it determines whether they need surgery or not
* A middle aged woman has symptoms of an upper respiratory tract infection. After taking the anamnesis and physical examination, you're certain that it's a viral infection. You reflexively want to order a CRP or leukocyte count, but you stop to consider: will the laboratory investigation be of value to the patient? You know that viral URTIs only cause mildly elevated inflammatory parametres, so that's likely what you'll find anyway. And even if the CRP is higher than you expect, you're certain enough that this is not a bacterial infection, so you won't be administering antibiotics anyway. So even after making the investigation, you'll most likely not be changing your management of this patient; managing their symptoms and encouraging rest, without antibiotics
** On the other hand, if the patient has symptoms which make it difficult to distinguish between viral and bacterial infection clinically, a laboratory investingation is merited, as it provides additional information which can aid in the diagnosis and therefore the treatment in this case
** Consider that many laboratories can analyse a pharyngeal swab for specific airway viruses. Would making such an investigation in this case change the management of the patient? In most cases no, as there is no specific treatment for most airway viruses anyway.


== Screening ==
The model "a safe diagnostic strategy", made by professor John Murtagh, involves five questions one should ask themselves during patient presentations:
Screening refers to using an investigation to detect a disease which has not yet caused symptoms, so-called subclinical disease, with the aim of initiating management as early as possible, to improve the prognosis.  Examples include:


* Regular [[mammography]] or [[cervical cytology]] in women
* What is the list of differential diagnoses, and which ones are most likely?
** Used to detect early or precursor [[breast cancer]] or precursor stages for [[cervical cancer]], respectively
* Which life-threatening or severe disorders are on the list of differential diagnoses that must not be missed?
* [[Faecal occult blood test]] in middle-aged/elderly
** Or "are there any red flags?"
** Used to detect early [[colorectal cancer]] or bleeding [[Colonic polyps|colon polyps]]
* Which disorders, which may present similarly, are usually overlooked?
* Screening for [[inborn errors of metabolism]] and [[developmental dysplasia of the hip]] in newborns
** Or "are there any diagnostic pitfalls I must avoid here?"
* [[Non-invasive prenatal test]] (NIPT) for trisomies during pregnancy
* Could the patient have one of the "great imitator" disorders? (Syphilis, tuberculosis, Lyme disease, SLE, +++)
Screening is indicated if the disorder has a high mortality or morbidity, and there is treatment available.
* Is the patient actually trying to tell me something else that I'm missing?


=== Screening tests ===
=== Using clinical findings and anamnesis to evaluate the pre-test probability ===
A screening test is most useful when it has high [[sensitivity]]. It would be great if a screening test also had high [[specificity]], but there is often a trade-off between sensitivity and specificity. Therefore, most screening tests have low specificity. As a result, screening tests produce few false negatives but many false positives, and many more false positives than true positives.
The probability of a person having a certain disorder depends on their symptoms and signs. For example, a person with sore throat and swollen tonsils with exudate have a much higher probability of having [[streptococcal tonsillitis]] than a person with sore throat but normal tonsils. Therefore, performing physical examination and taking a thorough anamnesis before considering whether to do a test is important. In some cases, a good physical examination and anamnesis may increase the pre-test probability to such an extent that the test becomes unnecessary.


Because many of those who have a positive screening test are false positives, positive screening test must always be confirmed by a more specific test.
For some disorders, researches have designed risk stratification tools which can help us determine the pre-test probability systematically. Examples are Wells criteria for [[DVT]] and [[PE]], Centor criteria for [[streptococcal pharyngitis]], Alvarado score for [[acute appendicitis]], and CHA2DS2-VASc score for [[thromboembolism]] in [[atrial fibrillation]]. These scores can give us the estimated pre-test probability in percent; for example, a CHA2DS2-VASc score of 3 equals a risk of thromboembolism of approximately 4.6%.


=== Advantages of screening ===
=== Considering test sensitivity ===
Screening may have many advantages. The main advantage, and the intention behind screening, is that treatment can be started at an earlier time, before symptoms even appear, which usually improves the prognosis considerably, and may allow for curative treatment, which may not have been an option if the disorder was not diagnosed at the asymptomatic stage.
Using a test with low sensitivity for the diagnosis of a disorder can lack value. Consider, for example, a rib fracture. One might think that a rib fracture should be evaluated with a radiograph, as most fractures are evaluated. However, a radiograph has very low sensitivity for rib fracture (60%), and so 40% of people with rib fracture will have no findings on an x-ray. Knowing this, you could not trust a negative radiograph to rule out rib fracture, and so it is not recommended for the evaluation of this disorder.


=== Disadvantages of screening ===
=== Considering how pre-test probability changes the test characteristics ===
Unfortunately, screening has many disadvantages as well.
Because positive and negative predictive values of a test depend on the pre-test probability, test may become more or less useful as the pre-test probability changes.


==== Low specificity of tests causing worry and more testing ====
For example, a negative D-dimer has a high negative predictive value for VTE. However, negative predictive value decreases with increasing pre-test probability. A person with a high pre-test probability (Wells score for PE of 7 or more) have a 40+% pre-test probability of PE. If the patient has a high pre-test probability, determined by their Wells score, the patient no longer has the same pre-test probability as the general population (which is low). The negative predictive value decreases, which makes a negative D-dimer unsuitable for ruling out PE in a person with high pre-test probability. In other words, a patient with a high Wells score but a negative D-dimer still has a relatively high probability of having PE.
Because screening tests necessarily have low specificity, there will be many false positives. Testing positive on a screening test, especially for cancer, leads to considerable worry for a person. Considering that most people who test positive on a screening test is false positive, the positive predictive value is low as well, meaning that the chance of having the disorder when testing positive is low. This concept is very difficult for laypeople to understand.


Because screening tests must be confirmed by a confirmatory test, screening for a disease always leads to more testing. In many cases, these tests are invasive, either entailing radiation exposure ([[CT]] scan) or complicated patient preparation and discomfort during the procedure ([[colonoscopy]]). In some cases, for example with NIPT testing, the confirmatory test ([[amniocentesis]] or [[chorionic villus sampling]]) is invasive and increase the risk of harm ([[abortion]] of the foetus in this case), which may lead to harm for people who are actually healthy.
=== Considering pre-test probability and disease severity ===
The more severe the suspected disorder is, the lower the pre-test probability needs to be before one should consider testing for it. This is because the consequences of missing a diagnosis is more severe, so the disadvantages of the test are weighed up for.


==== Early diagnosis may not always improve prognosis ====
For example, one would not test every person with a sore throat for [[streptococcal tonsillitis]], only if the pre-test probability is sufficiently high, usually more than 30%, as determined by a Centor score of 3 or more. However, one would test every person with significant microscopic haematuria for [[bladder cancer]] (usually by [[cystoscopy]]), despite a pre-test probability of only 5% (only 5% of people with significant microscopic haematuria have bladder cancer).
It is reasonable to assume that early diagnosis always improves the prognosis, but that is not always the case. In many cases, the cancer would develop so slowly that the person would never have known of it, or possibly only developed mild symptoms. However, cancer diagnosis almost always leads to aggressive treatment, which has its own effects on quality of life.


This is especially important for [[prostate cancer]], for example. Prostate cancer is relatively common in elderly, but research has shown that many who are treated for subclinical prostate cancer would never have developed symptoms of the cancer, and would rather have died peacefully, never knowing that they even had the cancer. Also important to consider that cancer treatment causes significant reduction in quality of life, which is especially unfortunate if the cancer would never have caused symptoms anyway.
=== Considering the treatment threshold ===
The treatment threshold is a theoretical level of disease probability (pre-test or post-test) where the disease is so likely that you would consider treatment to be indicated. Another way to think of it is "at what degree of disease uncertainty am I comfortable with initiating treatment?".


South Korea started screening for thyroid cancer in the late 20th century. Up until relatively recently, research showed that, while the incidince increased significantly (more cases of thyroid cancer were discovered), the mortality remained the same. In other words, screening detected more cases and lead to more people being treated for cancer, which is a burden to both the healthcare system and the individual, but screening could not demonstrate a reduction in mortality, which is arguably one of the most important goals of screening. This shows that screening can lead to significant overdiagnosis.<ref><nowiki>https://www.nejm.org/doi/full/10.1056/NEJMp1409841</nowiki></ref>
The treatment threshold is low if the treatment is harmless for healthy people and very efficacious for people with the assumed disease, for example [[Antihistamine|antihistamines]] in suspected [[allergic rhinitis]].


== Diagnosis ==
The treatment threshold is high if the treatment is harmful for healthy people ''or'' it is not very efficacious for people with the disease. This can occur for example in case of cancer (where treatment is very harmful, so the disease probability should be close to 100% before considering treatment) or in case of bacterial infections which are usually uncomplicated and self-limiting (like uncomplicated [[acute otitis media]] or [[acute sinusitis]]).
When an investigation is ordered for diagnosis, one should already have a list of differential diagnoses before ordering the test, and the test should be able to narrow down the list of differential diagnoses. It's important to consider the test's specificity, sensitivity, positive predictive value, and negative predictive value in this. There is no reason to perform an investigation if it doesn't help narrow doen the number of differential diagnoses.  


=== Using test characteristics wisely ===
If, based on the clinical findings, you find the pre-test probability to be sufficiently high that even a negative test will yield a post-test probability higher than the treatment threshold, testing does not influence the outcome, and so testing is unnecessary.
Because positive and negative predictive values depend on the prevalence of the disorder in the population, it's important to keep the prevalence of the disorder in mind.


For example, a negative D-dimer has a high negative predictive value for VTE. However, negative predictive value decreases with increasing prevalence. If the patient has a high pre-test probability, often determined by their Wells score (a scoring system used to determine the pre-test probability for DVT/PE), the patient no longer has the same pre-test probability as the general population (which is low). The
Alternatively, if you find the pre-test probability to be so low that despite a positive test the post-test probability remains lower than the treatment threshold, testing also does not influence the outcome, and so testing is unnecessary in this case as well. An example of this can be if a patient has a sore throat but you find no evidence of streptococcal tonsillitis, in which case even a positive rapid strep test won't make the diagnosis of streptococcal tonsillitis high enough that you would consider antibiotics.


== Follow-up and monitoring ==
== Follow-up and monitoring ==
Follow-up and monitoring of a disorder is also a common use of laboratory and imaging investigations. Examples include:
Follow-up and monitoring of a disorder is also a common use of laboratory and imaging investigations. Examples include:


* CRP or leukocyte count following antibiotic prescription to evaluate the treatment response
* Serial [[CRP]] or [[leukocyte]] count following [[antibiotic]] prescription to evaluate the treatment response
* Yearly brain MRI following removal of a meningeoma, to try and catch a recurrence early, before it causes symptoms
* Serial plasma [[sodium]] measurement following fluid restriction in assumed [[SIADH]]
* Yearly brain [[MRI]] following removal of a [[meningeoma]], to try and catch a recurrence early, before it causes symptoms


However, it's important to keep in mind the requirement of value for the patient. In the first scenario, there is value as a lack of normalisation of inflammatory parametres in a patient treated with antibiotic for a bacterial infection may be a sign that the antibiotic is ineffective, which may require administration of a different antibiotic. In the second scenario, there is also value, as the earlier one can catch recurrence of a meningeoma, the better the prognosis after treatment. However, if the patient is in a condition where they will not receive treatment anyway (for example, if they are terminal), monitoring is not of value to the patient.
However, it's important to keep in mind the requirement of value for the patient. In the first scenario, there is value as a lack of normalisation of inflammatory parametres in a patient treated with antibiotic for a bacterial infection may be a sign that the antibiotic is ineffective, which may require administration of a different antibiotic. In the third scenario, there is also value, as the earlier one can catch recurrence of a meningeoma, the better the prognosis after treatment. However, if the patient is in a condition where they will not receive treatment anyway (for example, if they are preterminal), monitoring is not of value to the patient.


== Evaluation of prognosis ==
== Evaluation of prognosis ==
In some cases, performing an investigation even though it won't change patient management can be useful if it provides information on patient prognosis. This is most common in case of patients with cancer.  
In some cases, performing an investigation even though it won't change patient management can be useful if it provides information on patient prognosis, for example the life expectancy. This is most common in case of patients with cancer.  


== External resources ==
== External resources ==


* [https://www.bmj.com/content/351/bmj.h5552 Explaining laboratory test results to patients: what the clinician needs to know]
* [https://www.bmj.com/content/351/bmj.h5552 Explaining laboratory test results to patients: what the clinician needs to know]
 
<noinclude>‎[[Category:Radiology]]
== References ==
[[Category:Radiology]]
[[Category:Laboratory Medicine]]
[[Category:Laboratory Medicine]]
[[Category:Public Health]]
[[Category:Public Health]]</noinclude>

Latest revision as of 11:58, 16 January 2024

When one orders a test (laboratory, imaging, or otherwise), it's important to have a predetermined purpose for the test and not just ordering tests willy-nilly. Tests are often invasive as well as time-consuming and expensive, and so they should be worth the risk, time, and expense. There is no point in ordering a test if the test result does not influence how you approach the patient.

Generally, investigations can be used for:

  • Screening
  • Diagnosis
  • Follow-up/monitoring
    • Monitoring progression/response to treatment
  • Evaluation of prognosis
    • Information regarding the likely outcome of the disease

Value to the patient

An investigation should have some form of value for the patient (except if done in a research setting or for epidemiological purpose, in which case the investigation has value for researchers, and in turn, future patients). The value to the patient should also weigh up for any negative consequences of the investigation.

Frail patients

Many frail patients, especially elderly, cannot or do not want to undergo certain tests or invasive procedures. Is there, for example, a point in evaluating a frail elderly person for cancer, if they do not want to or cannot undergo cancer treatment anyway? Take the following example:

A frail elderly patient living in an institution (like a nursing home) has a positive faecal occult blood test. The physician considers to refer them to colonoscopy, but stops to consider: how will a colonoscopy be of value to the patient? In their current state, even if the colonoscopy would show colorectal cancer, the patient would not be a candidate for any surgery or chemotherapy, so even if a diagnosis is made, nothing will change for the patient (except the stress of knowing they have cancer). In addition, colonoscopy is an invasive investigation which requires strict patient preparation, which can be difficult for a frail elderly to perform or even survive.

If they have colorectal cancer and it grows and eventually causes intestinal obstruction, colonoscopy may be indicated for stenting the bowel, in which case the colonoscopy would have value for the patient as palliative therapy. As such, one could note that the patient may have colorectal cancer, and only refer them to colonoscopy if intestinal obstruction is suspected at a later time.

One can also argue that even performing a faecal occult blood test in this case has no value for the patient, because the next step after a positive test would be a colonoscopy, a procedure which would not be of value to the patient anyway.

Patient management is the same regardless of test result

In some cases, it may be temping to order an investigation to gain more information, but it's important to consider whether that information is of value or not. Take the following example:

A young male has had lower back pain for a few days. The pain is not severe, and there are no red flags for cauda equina syndrome. He wants an MRI to know what's going on, but the physician stops to consider: how will an MRI be of value to the patient? The patient may or may not have a herniated disc, but even if they do, a herniated disc without red flags isn't an indication for surgery anyway. As such, whether the MRI shows a herniated disc or not, the management will be the same (no surgery, only physical therapy and pain relief), and the MRI is therefore of no value to the patient (and it is resource-intensive).

On the other hand, if the patient has debilitating pain or there are red flags present, he may have cauda equina syndrome, in which case surgery is indicated. In this case, MRI has value: it determines whether they need surgery or not.

Another example:

A middle aged woman has symptoms of an upper respiratory tract infection. After taking the anamnesis and physical examination, you're certain that it's a viral infection. You reflexively want to order a CRP or leukocyte count, but you stop to consider: will the laboratory investigation likely be of value to the patient? You know that viral URTIs only cause mildly elevated inflammatory parametres, so that's likely what you'll find anyway. And even if the CRP is higher than you expect, you're certain enough that this is not a bacterial infection, so you won't be administering antibiotics anyway. So even after making the investigation, you'll most likely not be changing your management of this patient; managing their symptoms and encouraging rest, without antibiotics.

On the other hand, if the patient has symptoms which make it difficult to distinguish between viral and bacterial infection clinically, a laboratory investingation is merited, as it provides additional information which can aid in the diagnosis and therefore the treatment in this case.

Consider that many laboratories can analyse a pharyngeal swab for specific airway viruses. Would making such an investigation in this case change the management of the patient? In most cases no, as there is no specific treatment for most airway viruses anyway.

Diagnosis

When an investigation is ordered for diagnosis, one should already have a list of differential diagnoses before ordering the test, and the test should be able to narrow down the list of differential diagnoses. It's important to consider the test's specificity, sensitivity, positive predictive value, and negative predictive value in this. There is no reason to perform an investigation if it doesn't help narrow down the number of differential diagnoses or doesn't validate your tentative diagnosis.

This article leans heavily on statistical terms like probability and thresholds. In real-life, the exact probability and thresholds cannot be known in most circumstances. Instead, we think of these factors in approximate terms based not on statistical analysis but our own experience and knowledge.

Approach to diagnosis

When a patient is presented with symptoms or clinical findings, one should formulate a list of differential diagnoses which could be underlying. Often, this is not a conscious process but rather an unconscious one.

The model "a safe diagnostic strategy", made by professor John Murtagh, involves five questions one should ask themselves during patient presentations:

  • What is the list of differential diagnoses, and which ones are most likely?
  • Which life-threatening or severe disorders are on the list of differential diagnoses that must not be missed?
    • Or "are there any red flags?"
  • Which disorders, which may present similarly, are usually overlooked?
    • Or "are there any diagnostic pitfalls I must avoid here?"
  • Could the patient have one of the "great imitator" disorders? (Syphilis, tuberculosis, Lyme disease, SLE, +++)
  • Is the patient actually trying to tell me something else that I'm missing?

Using clinical findings and anamnesis to evaluate the pre-test probability

The probability of a person having a certain disorder depends on their symptoms and signs. For example, a person with sore throat and swollen tonsils with exudate have a much higher probability of having streptococcal tonsillitis than a person with sore throat but normal tonsils. Therefore, performing physical examination and taking a thorough anamnesis before considering whether to do a test is important. In some cases, a good physical examination and anamnesis may increase the pre-test probability to such an extent that the test becomes unnecessary.

For some disorders, researches have designed risk stratification tools which can help us determine the pre-test probability systematically. Examples are Wells criteria for DVT and PE, Centor criteria for streptococcal pharyngitis, Alvarado score for acute appendicitis, and CHA2DS2-VASc score for thromboembolism in atrial fibrillation. These scores can give us the estimated pre-test probability in percent; for example, a CHA2DS2-VASc score of 3 equals a risk of thromboembolism of approximately 4.6%.

Considering test sensitivity

Using a test with low sensitivity for the diagnosis of a disorder can lack value. Consider, for example, a rib fracture. One might think that a rib fracture should be evaluated with a radiograph, as most fractures are evaluated. However, a radiograph has very low sensitivity for rib fracture (60%), and so 40% of people with rib fracture will have no findings on an x-ray. Knowing this, you could not trust a negative radiograph to rule out rib fracture, and so it is not recommended for the evaluation of this disorder.

Considering how pre-test probability changes the test characteristics

Because positive and negative predictive values of a test depend on the pre-test probability, test may become more or less useful as the pre-test probability changes.

For example, a negative D-dimer has a high negative predictive value for VTE. However, negative predictive value decreases with increasing pre-test probability. A person with a high pre-test probability (Wells score for PE of 7 or more) have a 40+% pre-test probability of PE. If the patient has a high pre-test probability, determined by their Wells score, the patient no longer has the same pre-test probability as the general population (which is low). The negative predictive value decreases, which makes a negative D-dimer unsuitable for ruling out PE in a person with high pre-test probability. In other words, a patient with a high Wells score but a negative D-dimer still has a relatively high probability of having PE.

Considering pre-test probability and disease severity

The more severe the suspected disorder is, the lower the pre-test probability needs to be before one should consider testing for it. This is because the consequences of missing a diagnosis is more severe, so the disadvantages of the test are weighed up for.

For example, one would not test every person with a sore throat for streptococcal tonsillitis, only if the pre-test probability is sufficiently high, usually more than 30%, as determined by a Centor score of 3 or more. However, one would test every person with significant microscopic haematuria for bladder cancer (usually by cystoscopy), despite a pre-test probability of only 5% (only 5% of people with significant microscopic haematuria have bladder cancer).

Considering the treatment threshold

The treatment threshold is a theoretical level of disease probability (pre-test or post-test) where the disease is so likely that you would consider treatment to be indicated. Another way to think of it is "at what degree of disease uncertainty am I comfortable with initiating treatment?".

The treatment threshold is low if the treatment is harmless for healthy people and very efficacious for people with the assumed disease, for example antihistamines in suspected allergic rhinitis.

The treatment threshold is high if the treatment is harmful for healthy people or it is not very efficacious for people with the disease. This can occur for example in case of cancer (where treatment is very harmful, so the disease probability should be close to 100% before considering treatment) or in case of bacterial infections which are usually uncomplicated and self-limiting (like uncomplicated acute otitis media or acute sinusitis).

If, based on the clinical findings, you find the pre-test probability to be sufficiently high that even a negative test will yield a post-test probability higher than the treatment threshold, testing does not influence the outcome, and so testing is unnecessary.

Alternatively, if you find the pre-test probability to be so low that despite a positive test the post-test probability remains lower than the treatment threshold, testing also does not influence the outcome, and so testing is unnecessary in this case as well. An example of this can be if a patient has a sore throat but you find no evidence of streptococcal tonsillitis, in which case even a positive rapid strep test won't make the diagnosis of streptococcal tonsillitis high enough that you would consider antibiotics.

Follow-up and monitoring

Follow-up and monitoring of a disorder is also a common use of laboratory and imaging investigations. Examples include:

  • Serial CRP or leukocyte count following antibiotic prescription to evaluate the treatment response
  • Serial plasma sodium measurement following fluid restriction in assumed SIADH
  • Yearly brain MRI following removal of a meningeoma, to try and catch a recurrence early, before it causes symptoms

However, it's important to keep in mind the requirement of value for the patient. In the first scenario, there is value as a lack of normalisation of inflammatory parametres in a patient treated with antibiotic for a bacterial infection may be a sign that the antibiotic is ineffective, which may require administration of a different antibiotic. In the third scenario, there is also value, as the earlier one can catch recurrence of a meningeoma, the better the prognosis after treatment. However, if the patient is in a condition where they will not receive treatment anyway (for example, if they are preterminal), monitoring is not of value to the patient.

Evaluation of prognosis

In some cases, performing an investigation even though it won't change patient management can be useful if it provides information on patient prognosis, for example the life expectancy. This is most common in case of patients with cancer.

External resources

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