screening (10) Flashcards

1
Q

what does screening aim to do

A

identify individualist early stages of disease to provide corresponding interventions

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2
Q

pros of screening

A

better prognosis, improved population health, reduction in further treatment costs

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3
Q

cons of screening

A

not useful for rare diseases or diseases with short preclinical/ asymtopmatic phase

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4
Q

when is screening not useful

A

if it is of poor quality or expensive, if early treatment doesn’t effect outcome ie not beneficial

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5
Q

screening for rare diseases

A

false positives can cause anxiety and also exposure to unnecessary risks eg radiation from further treatment

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6
Q

what to weigh up when screening

A

if cost and benefits outweigh the harm

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7
Q

true and false positives

A

true positives are good due to early intervention

false positives can cause invasive further treatment and psychological harm

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8
Q

true and false negatives

A

true negative is good

false positive is bad as disease not picked up could become more severe, also can endorse risky behaviours

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9
Q

lead time

A

time between screening and when ‘normal’ diagnosis would occur

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10
Q

lead time bias

A

measure of survival from screened diagnosis inflates effectiveness as more time to treat and react to disease

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11
Q

solution to lead time bias

A

measure survival time from baseline, use randomisation

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12
Q

length time bias

A

slow progressing disease easier to be picked up from screening, often less severe and have longer survival

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13
Q

selection bias

A

individuals who get screened more likely to be health conscious

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14
Q

challenges to screening

A

number registered
language or financial barriers
non attendees usually from poorest groups

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15
Q

what makes ‘good’ screening

A

cheap and easily implemented

accurate enough vs gold standard

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16
Q

what is sensitivity

A

number with disease correctly identified

17
Q

how to calculate sensitivity

A

number true positives / total with disease

18
Q

specificity

A

number without disease correctly identified

19
Q

calculate specificity

A

number try negatives / total without disease

20
Q

positive predictive value PPV

A

if screened positive, likelihood they have disease

21
Q

calculate PPV

A

number true positives / total number who screened positive

22
Q

negative predictive value NPV

A

if screened negative chance they don’t have the disease

23
Q

calculate NPV

A

number true negative / total number who screened negative

24
Q

calculate false negative rate

A

number false negative / number with disease

25
Q

false positive rate

A

number of false positives / number without disease

26
Q

when does prevalence make a difference

A

PPV and NPV affected by prevalence but sensitivity and specificity are not

27
Q

too stringent or too lenient

A

stringent = low sensitivity

too lenient = low specificity