Concept · medicine
Diagnostic Accuracy
Follow Diagnostic Accuracy — see important new research and changes in evidence.Change log
What changed
Dated edits to this page's evidence: studies added or removed from a claim, claims added or withdrawn, and new explanations tagged here. Rewordings are not listed.
Smartphone photoplethysmography detected atrial fibrillation with sensitivity about 95.6% and specificity about 96.6% versus ECG in an analysed clinic sample (adequate signal required; pacing excluded).
- Removed a supporting study: Rapid gram-positive blood culture ID
- Removed a supporting study: How well does CA125 find ovarian cancer in GP care?
- Added a scope qualifier: Blood GFAP and NfL predict dementia years ahead
- Added a scope qualifier: How well does CA125 find ovarian cancer in GP care?
A multiplex molecular assay on monomicrobial blood cultures identified Staphylococcus at genus level with sensitivity about 99.4% and specificity about 99.7% in a large evaluated set.
- New claim
- Added a supporting study: Rapid gram-positive blood culture ID
- Added a scope qualifier: Smartphone PPG to detect atrial fibrillation
- Added a scope qualifier: Can a rapid test diagnose sickle cell at the bedside?
In GP care, CA125 ≥35 U/ml for ovarian cancer showed sensitivity about 77%, specificity about 93.8%, and AUC about 0.92, but PPV was only about 10.1% because incidence was about 0.9%—illustrating prevalence’s grip on predictive value.
- New claim
- Added a supporting study: How well does CA125 find ovarian cancer in GP care?
- Added a scope qualifier: Smartphone PPG to detect atrial fibrillation
- Added a scope qualifier: Diabetes prevalence and risk-score accuracy
Diabetes risk scores in an Amsterdam sample showed AUCs about 0.74–0.80 with numbers-needed-to-screen of 3–7 depending on the outcome definition—accuracy metrics tied to local prevalence and cut-offs.
- New claim
- Added a supporting study: Diabetes prevalence and risk-score accuracy
- Added a scope qualifier: Blood GFAP and NfL predict dementia years ahead
- Added a scope qualifier: How well does CA125 find ovarian cancer in GP care?
In UK Biobank, higher baseline plasma GFAP and NfL were associated with roughly doubled hazards of incident dementia over ~13 years, with incremental discrimination when added to demographic risk scores—prognostic biomarker performance, not a bedside diagnostic rule-in test.
- New claim
- Added a supporting study: Blood GFAP and NfL predict dementia years ahead
- Added a scope qualifier: Rising frailty flags one-year death risk
- Added a scope qualifier: Smartphone PPG to detect atrial fibrillation
Other validated tools in this set include a point-of-care sickle-cell device detecting HbS/HbC at low percentages suitable for neonates, StEP pinprick signs highly sensitive/specific for neuropathic vs non-neuropathic pain in specialist clinics, and rapidly rising electronic frailty index trajectories associated with doubled 12-month mortality versus stable frailty.
- New claim
- Added a supporting study: StEP pain-subtype assessment
- Added a supporting study: Rising frailty flags one-year death risk
- Added a supporting study: Can a rapid test diagnose sickle cell at the bedside?
- Added a scope qualifier: Blood GFAP and NfL predict dementia years ahead
- Added a scope qualifier: How well does CA125 find ovarian cancer in GP care?
241 enrolled; 223 analysed. Sensitivity 95.6%, specificity 96.6% vs ECG.
- Claim withdrawn
Among 1,157 monomicrobial cultures, Staphylococcus genus sensitivity was 99.4% and specificity 99.7%; staphylococci dominated the culture set.
- Claim withdrawn
Ovarian cancer incidence was 0.9%. At ≥35 U/ml, PPV was 10.1%, sensitivity 77%, specificity 93.8%, and AUC 0.92. Performance and cancer mix varied by age; elevated CA125 also related to non-ovarian cancers.
- Claim withdrawn
Prevalence was 25.6%, 12.7%, and 6.8% respectively. Risk-score AUCs were 0.74, 0.80, and 0.78 with NNS 3, 5, and 7.
- Claim withdrawn
Rapidly rising frailty (≈0.01 eFI/month) doubled 12-month death risk vs stable frailty; reweighted, this class (~1.1% of population) predicted 1-year mortality with 99.1% specificity.
- Claim withdrawn
Point-of-care classification accuracy (AF, blood culture ID, sickle cell, pain subtype) is not the same claim as low-prevalence screening PPV or long-horizon prognostic discrimination. Mixing sensitivities with hazards or PPVs invents a false head-to-head.
- Added a supporting study: Blood GFAP and NfL predict dementia years ahead
- Removed a supporting study: Rapid gram-positive blood culture ID
- Marked as a scope tension, not a disagreement
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High sensitivity/specificity in a selected clinic sample does not guarantee useful predictive values in a low-prevalence screening population—the CA125 GP analysis is the cautionary case in this library.
- New tension
- Added a supporting study: Smartphone PPG to detect atrial fibrillation
- Added a supporting study: How well does CA125 find ovarian cancer in GP care?
If sensitivity and specificity are high, positive predictive value will be high too.
- Added a misconception
Plasma NfL/GFAP dementia associations are the same kind of result as a smartphone AF diagnostic study.
- Added a misconception
Assay accuracy automatically means better patient outcomes.
- Added a misconception
Diagnostic Accuracy findings always generalise to every clinic.
- Removed a misconception
- Concept page published
Diagnostic accuracy studies estimate how well a test classifies disease—often via sensitivity, specificity, predictive values, or discrimination (AUC)—against a reference standard or outcome. Related work includes risk scores and prognostic biomarkers that forecast future events rather than confirm current disease.
A bedside assay with 95% sensitivity, a low-prevalence screening PPV, and a plasma protein that forecasts dementia years ahead are all “accuracy-ish,” but they answer different clinical questions and break in different ways.
Evidence
What the evidence shows
Drawn from 8 studies in this library. Each finding starts with a plain-language takeaway, then the denser detail. Supports means evidence for a finding; Challenges means evidence against a stated position; Qualifies marks scope with a short note on each study’s contribution. Challenged positions are labeled — they are not findings.
Phone pulse waveforms can detect atrial fibrillation accurately versus ECG in clinic samples.
Smartphone photoplethysmography detected atrial fibrillation with sensitivity about 95.6% and specificity about 96.6% versus ECG in an analysed clinic sample (adequate signal required; pacing excluded).
- How well does CA125 find ovarian cancer in GP care?— different setting — low-prevalence GP screening PPV, not clinic AF vs ECG
- Blood GFAP and NfL predict dementia years ahead— different question — long-horizon prognosis, not point-of-care arrhythmia detection
Study Role Design N Population Outcome Smartphone PPG to detect atrial fibrillation Supports Cross-sectionalDiagnostic accuracy vs 12-lead ECG in primary care N=223 · 241 enrolled; 223 analysed after exclusions Primary-care patients screened for atrial fibrillation with FibriCheck PPG Sensitivity and specificity of mobile PPG for AF vs 12-lead ECG How well does CA125 find ovarian cancer in GP care? Qualifiesdifferent setting — low-prevalence GP screening PPV, not clinic AF vs ECG CohortPopulation-based primary-care EHR cohort N=50780 · Women with CA125 tested in English primary care Women having CA125 measured in English general practice PPV, sensitivity, specificity, and AUC of CA125 ≥35 U/ml for ovarian cancer Blood GFAP and NfL predict dementia years ahead Qualifiesdifferent question — long-horizon prognosis, not point-of-care arrhythmia detection CohortUK Biobank prospective plasma GFAP/NfL with registry dementia follow-up N=48542 · 1,312 incident all-cause dementia over ~13 years UK Biobank adults with baseline Olink plasma GFAP and NfL Incident all-cause dementia / ADRD HRs and prediction AUC for GFAP and NfL A multiplex assay can identify Staphylococcus from blood cultures with very high accuracy.
A multiplex molecular assay on monomicrobial blood cultures identified Staphylococcus at genus level with sensitivity about 99.4% and specificity about 99.7% in a large evaluated set.
- Can a rapid test diagnose sickle cell at the bedside?— different target — sickle-cell bedside detection, not blood-culture ID
- Smartphone PPG to detect atrial fibrillation— different modality — PPG AF screening, not microbiology ID
In GP care, CA125 looks accurate but a positive rarely means ovarian cancer when disease is rare.
In GP care, CA125 ≥35 U/ml for ovarian cancer showed sensitivity about 77%, specificity about 93.8%, and AUC about 0.92, but PPV was only about 10.1% because incidence was about 0.9%—illustrating prevalence’s grip on predictive value.
- Smartphone PPG to detect atrial fibrillation— higher-prevalence clinic AF sample — PPV/NPV not transportable as raw sensitivities
- Diabetes prevalence and risk-score accuracy— related lesson — risk-score AUCs with number-needed-to-screen trade-offs
Study Role Design N Population Outcome How well does CA125 find ovarian cancer in GP care? Supports CohortPopulation-based primary-care EHR cohort N=50780 · Women with CA125 tested in English primary care Women having CA125 measured in English general practice PPV, sensitivity, specificity, and AUC of CA125 ≥35 U/ml for ovarian cancer Smartphone PPG to detect atrial fibrillation Qualifieshigher-prevalence clinic AF sample — PPV/NPV not transportable as raw sensitivities Cross-sectionalDiagnostic accuracy vs 12-lead ECG in primary care N=223 · 241 enrolled; 223 analysed after exclusions Primary-care patients screened for atrial fibrillation with FibriCheck PPG Sensitivity and specificity of mobile PPG for AF vs 12-lead ECG Diabetes prevalence and risk-score accuracy Qualifiesrelated lesson — risk-score AUCs with number-needed-to-screen trade-offs Cross-sectionalSUNSET Amsterdam population sample; ethnicity-stratified screening criteria N=1434 · 339 Hindustani Surinamese, 605 African Surinamese, 490 Dutch Amsterdam adults aged 35–60 (Hindustani Surinamese, African Surinamese, Dutch) Diabetes prevalence and risk-score AUC / numbers-needed-to-screen by ethnicity Diabetes risk scores trade accuracy against how many people you must screen locally.
Diabetes risk scores in an Amsterdam sample showed AUCs about 0.74–0.80 with numbers-needed-to-screen of 3–7 depending on the outcome definition—accuracy metrics tied to local prevalence and cut-offs.
- How well does CA125 find ovarian cancer in GP care?— different disease and prevalence regime — ovarian cancer screening PPV
- Blood GFAP and NfL predict dementia years ahead— different task — prognostic plasma proteins, not cross-sectional diabetes scoring
Study Role Design N Population Outcome Diabetes prevalence and risk-score accuracy Supports Cross-sectionalSUNSET Amsterdam population sample; ethnicity-stratified screening criteria N=1434 · 339 Hindustani Surinamese, 605 African Surinamese, 490 Dutch Amsterdam adults aged 35–60 (Hindustani Surinamese, African Surinamese, Dutch) Diabetes prevalence and risk-score AUC / numbers-needed-to-screen by ethnicity How well does CA125 find ovarian cancer in GP care? Qualifiesdifferent disease and prevalence regime — ovarian cancer screening PPV CohortPopulation-based primary-care EHR cohort N=50780 · Women with CA125 tested in English primary care Women having CA125 measured in English general practice PPV, sensitivity, specificity, and AUC of CA125 ≥35 U/ml for ovarian cancer Blood GFAP and NfL predict dementia years ahead Qualifiesdifferent task — prognostic plasma proteins, not cross-sectional diabetes scoring CohortUK Biobank prospective plasma GFAP/NfL with registry dementia follow-up N=48542 · 1,312 incident all-cause dementia over ~13 years UK Biobank adults with baseline Olink plasma GFAP and NfL Incident all-cause dementia / ADRD HRs and prediction AUC for GFAP and NfL Higher blood GFAP and NfL associate with later dementia risk — prognosis, not same-day diagnosis.
In UK Biobank, higher baseline plasma GFAP and NfL were associated with roughly doubled hazards of incident dementia over ~13 years, with incremental discrimination when added to demographic risk scores—prognostic biomarker performance, not a bedside diagnostic rule-in test.
- Smartphone PPG to detect atrial fibrillation— different task — detecting current AF vs ECG, not forecasting dementia
- Rising frailty flags one-year death risk— related prognostic framing — frailty trajectory vs death, not plasma NfL
Study Role Design N Population Outcome Blood GFAP and NfL predict dementia years ahead Supports CohortUK Biobank prospective plasma GFAP/NfL with registry dementia follow-up N=48542 · 1,312 incident all-cause dementia over ~13 years UK Biobank adults with baseline Olink plasma GFAP and NfL Incident all-cause dementia / ADRD HRs and prediction AUC for GFAP and NfL Smartphone PPG to detect atrial fibrillation Qualifiesdifferent task — detecting current AF vs ECG, not forecasting dementia Cross-sectionalDiagnostic accuracy vs 12-lead ECG in primary care N=223 · 241 enrolled; 223 analysed after exclusions Primary-care patients screened for atrial fibrillation with FibriCheck PPG Sensitivity and specificity of mobile PPG for AF vs 12-lead ECG Rising frailty flags one-year death risk Qualifiesrelated prognostic framing — frailty trajectory vs death, not plasma NfL CohortEnglish primary-care EHR; monthly eFI trajectories before death vs matched controls N=26298 · 13,149 decedents and 13,149 matched controls English primary-care patients with electronic frailty index trajectories 12-month mortality risk by rapidly rising vs stable frailty class Other tools (sickle cell, pain subtype, frailty trajectories) answer their own accuracy questions.
Other validated tools in this set include a point-of-care sickle-cell device detecting HbS/HbC at low percentages suitable for neonates, StEP pinprick signs highly sensitive/specific for neuropathic vs non-neuropathic pain in specialist clinics, and rapidly rising electronic frailty index trajectories associated with doubled 12-month mortality versus stable frailty.
- How well does CA125 find ovarian cancer in GP care?— different prevalence and pathway — GP ovarian-cancer screening
- Blood GFAP and NfL predict dementia years ahead— different prognostic biomarker — plasma proteins for dementia
Open questions
Tensions and limits
Some items are genuine disagreements on the same question. Others mark different assays, populations, or outcomes — limits on how far one study travels — not a forced fight between papers.
Point-of-care classification accuracy (AF, blood culture ID, sickle cell, pain subtype) is not the same claim as low-prevalence screening PPV or long-horizon prognostic discrimination. Mixing sensitivities with hazards or PPVs invents a false head-to-head.
- Smartphone PPG to detect atrial fibrillation
- How well does CA125 find ovarian cancer in GP care?
- Blood GFAP and NfL predict dementia years ahead
Study Role Design N Population Outcome Smartphone PPG to detect atrial fibrillation Supports Cross-sectionalDiagnostic accuracy vs 12-lead ECG in primary care N=223 · 241 enrolled; 223 analysed after exclusions Primary-care patients screened for atrial fibrillation with FibriCheck PPG Sensitivity and specificity of mobile PPG for AF vs 12-lead ECG How well does CA125 find ovarian cancer in GP care? Supports CohortPopulation-based primary-care EHR cohort N=50780 · Women with CA125 tested in English primary care Women having CA125 measured in English general practice PPV, sensitivity, specificity, and AUC of CA125 ≥35 U/ml for ovarian cancer Blood GFAP and NfL predict dementia years ahead Supports CohortUK Biobank prospective plasma GFAP/NfL with registry dementia follow-up N=48542 · 1,312 incident all-cause dementia over ~13 years UK Biobank adults with baseline Olink plasma GFAP and NfL Incident all-cause dementia / ADRD HRs and prediction AUC for GFAP and NfL High sensitivity/specificity in a selected clinic sample does not guarantee useful predictive values in a low-prevalence screening population—the CA125 GP analysis is the cautionary case in this library.
Study Role Design N Population Outcome How well does CA125 find ovarian cancer in GP care? Supports CohortPopulation-based primary-care EHR cohort N=50780 · Women with CA125 tested in English primary care Women having CA125 measured in English general practice Predictive values of CA125 for ovarian cancer in low-prevalence primary care Smartphone PPG to detect atrial fibrillation Supports Cross-sectionalDiagnostic accuracy vs 12-lead ECG in primary care N=223 · 241 enrolled; 223 analysed after exclusions Primary-care patients screened for atrial fibrillation with FibriCheck PPG Sensitivity/specificity of PPG for AF in a selected primary-care sample
Common misconceptions
If sensitivity and specificity are high, positive predictive value will be high too.
CA125 in GP care kept relatively high specificity while PPV stayed about 10% because ovarian cancer was rare (~0.9%). Prevalence drives predictive values.
Plasma NfL/GFAP dementia associations are the same kind of result as a smartphone AF diagnostic study.
NfL/GFAP here are long-horizon prognostic associations with incident dementia. The PPG study classifies current AF against ECG. Different tasks and metrics.
Assay accuracy automatically means better patient outcomes.
Blood-culture ID and similar papers evaluate analytic/clinical classification performance; they do not by themselves prove that faster or more accurate reporting reduces mortality.
Exam-style questions
Short-answer questions that ask you to explain or compare, not recall.
Why can a test with 94% specificity still have a disappointing PPV?
When disease is rare, even modest false-positive rates create many false positives relative to true positives. CA125 in GP care is the worked example (PPV ~10% at ~0.9% incidence).
How should you label NfL/GFAP dementia results on a diagnostic-accuracy page?
As prognostic discrimination / hazard associations for future dementia—not as a point-of-care rule-in test with sensitivity/specificity against a current gold-standard diagnosis.
The studies
8 studies in this library bear on Diagnostic Accuracy, ordered by citations.
- StEP pain-subtype assessment
A structured interview-plus-exam tool (StEP) was developed and validated to separate neuropathic/radicular from non-neuropathic axial low-back pain.
- How well does CA125 find ovarian cancer in GP care?
In UK primary care, CA125 ≥35 U/ml had high NPV but only about 10% PPV for ovarian cancer, and elevated values also flagged other cancers.
- Blood GFAP and NfL predict dementia years ahead
In 48,542 UK Biobank participants followed ~13 years, elevated plasma GFAP and NfL preceded dementia up to 15 years and improved prediction beyond CAIDE/DRS risk scores (AUC up to ~0.89).
- Smartphone PPG to detect atrial fibrillation
FibriCheck PPG showed ~96% sensitivity and specificity versus cardiologist ECG on analysable traces.
- Rising frailty flags one-year death risk
Rapid monthly rises in the electronic frailty index marked older adults twice as likely to die within a year, with high specificity.
- Diabetes prevalence and risk-score accuracy
Hindustani Surinamese had ~26% diabetes prevalence; a clinical risk score showed moderate-to-good AUCs (~0.74–0.80) across ethnic groups.
- Rapid gram-positive blood culture ID
A microarray panel identified Staphylococcus from positive blood cultures with ~99% sensitivity and specificity versus culture.
- Can a rapid test diagnose sickle cell at the bedside?
Sickle SCAN, a point-of-care immunoassay, was validated against laboratory gold standards for detecting hemoglobin S and related genotypes.
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