Our Sources
Every question we ask in Carify's analysis questionnaires is grounded in peer-reviewed medical literature, clinical guidelines, and established medical databases. Here's what informed each section.
Cancer
The fields, options, and categories in our cancer analysis form.
Cancer Types
Our 15 cancer type categories were selected based on prevalence data and treatment pathway differentiation. Each type has distinct staging, mutation profiles, and treatment protocols that require different questionnaire fields.
NCI SEER Cancer Statistics Review
Prevalence and incidence data used to prioritize which cancer types to include.
American Cancer Society — Cancer Facts & Figures 2025
Annual cancer statistics informing our type categorization.
WHO International Classification of Diseases for Oncology (ICD-O-3)
Standard classification system for cancer site and morphology.
Cancer Staging
We use the simplified AJCC stage groupings (I–IV) because they're the most universally understood by patients and map directly to treatment decision-making. The "unknown" option accounts for cases where staging is pending or unclear.
Genetic Mutations & Biomarkers
The 14 mutations and biomarkers in our questionnaire were selected because they directly influence treatment selection — each one either qualifies or disqualifies the patient for specific targeted therapies or immunotherapies.
NCCN Biomarkers Compendium
Definitive guide for which biomarkers guide treatment decisions in each cancer type.
OncoKB — MSK Precision Oncology Knowledge Base
Curated database of cancer gene alterations and their treatment implications. Used to prioritize which mutations to include.
FDA Table of Pharmacogenomic Biomarkers
FDA-recognized biomarkers tied to drug labeling — confirms clinical relevance of each mutation we track.
COSMIC — Catalogue of Somatic Mutations in Cancer
Comprehensive database of somatic mutations. Used to validate mutation prevalence across cancer types.
My Cancer Genome — Vanderbilt-Ingram Cancer Center
Clinically curated resource linking specific mutations to available therapies.
Metastatic Disease
Metastatic status fundamentally changes treatment approach — from curative to management-focused in many cases. We ask about specific metastatic sites because treatment varies significantly based on where the cancer has spread.
Treatment Tracking
We separate current from previous treatments because treatment history directly affects which options remain available. Many drugs can't be re-used, and prior response patterns help predict future treatment efficacy.
NCCN Treatment Guidelines — All Cancer Types
Standard-of-care treatment sequences and line-of-therapy recommendations.
ASCO Treatment Guidelines
Evidence-based clinical practice guidelines for cancer treatment.
NCI Drug Information — A to Z List
Comprehensive drug reference used to inform treatment field placeholders and validation.
Side Effects & Deficiencies
Side effects shape quality of life and can force treatment changes. Enzyme deficiencies (like DPD) are critical safety flags — some can make standard chemotherapy drugs lethal.
NCI Common Terminology Criteria for Adverse Events (CTCAE)
Standard grading system for treatment side effects. Informed our side effect categories.
Clinical Pharmacogenetics Implementation Consortium (CPIC) — DPD/DPYD Guidelines
Critical safety guidelines for DPD deficiency and fluoropyrimidine chemotherapy.
PharmGKB — Pharmacogenomics Knowledge Base
Database linking genetic variations to drug response — informs our deficiency tracking.
Lab Results
Lab values are the most objective data points in a patient's record. Tracking tumor markers (CEA, CA-125, PSA), blood counts, and organ function tests over time reveals treatment response and emerging concerns.
ASCO Tumor Marker Guidelines
Guidelines on which tumor markers to monitor by cancer type.
NCI Understanding Laboratory Tests
Patient-friendly guide to lab tests in cancer care. Informed our lab result field design.
Lab Tests Online — AACC
Comprehensive lab test reference with reference ranges and clinical significance.
Family History
Family history can reveal hereditary cancer syndromes (Lynch, BRCA, Li-Fraumeni) that change screening, prevention, and treatment approaches — not just for the patient, but for their family members.
NCCN Genetic/Familial High-Risk Assessment Guidelines
Guidelines for when family history warrants genetic testing and altered management.
NCI Genetics of Cancer (PDQ)
Comprehensive overview of hereditary cancer syndromes and their clinical implications.
CDC Family Health History and Cancer
Public health perspective on family history as a risk factor. Informed our prompt phrasing.
Autoimmune Conditions
Rheumatoid arthritis, lupus, MS, Crohn's, and other autoimmune conditions.
Autoimmune Disease Classification
We categorize autoimmune conditions by affected system (systemic, joint, GI, neurological, skin, endocrine) because treatment pathways differ fundamentally based on which organs are involved and whether the disease is systemic or organ-specific.
American College of Rheumatology — Disease Guidelines
Evidence-based guidelines for rheumatologic and autoimmune conditions. Informed our disease categorization and severity assessment.
National Institute of Allergy and Infectious Diseases — Autoimmune Diseases
NIH overview of autoimmune disease mechanisms and classification used to structure our intake categories.
American Autoimmune Related Diseases Association (AARDA)
Patient advocacy resource covering 100+ autoimmune diseases. Informed our condition type list and patient-facing language.
Disease Activity & Severity
Unlike cancer staging, autoimmune diseases use disease activity scores and flare patterns. We track remission status, flare frequency, and severity because these directly determine whether treatment should escalate, maintain, or taper.
DAS28 — Disease Activity Score Calculator
Standard disease activity measure for rheumatoid arthritis. Informed our severity assessment approach for joint-predominant conditions.
SLEDAI — Systemic Lupus Activity Measure
Validated lupus activity index. Influenced how we assess disease activity in systemic autoimmune conditions.
Mayo Score / CDAI — IBD Activity Indices
Standard activity indices for ulcerative colitis and Crohn's disease used in our GI autoimmune assessment.
Immunosuppressive Therapies
Autoimmune treatment follows a step-up approach: conventional DMARDs, then biologics, then targeted small molecules. We track which therapies have been tried because prior treatment failures determine which options remain available.
ACR Guidelines for RA Management (2021)
Treat-to-target guidelines establishing the step-up therapy approach we use for treatment sequencing.
AGA Clinical Practice Guidelines — IBD
American Gastroenterological Association guidelines for inflammatory bowel disease treatment.
FDA Approved Biologics for Autoimmune Diseases
FDA biologics database used to validate our treatment tracking categories and drug lists.
Autoantibody Panels & Lab Monitoring
Autoantibodies (ANA, anti-dsDNA, RF, anti-CCP) are diagnostic cornerstones and influence prognosis. We track inflammatory markers (CRP, ESR) and organ function labs because they reveal disease activity and medication safety.
Cardiac Conditions
Heart failure, coronary artery disease, arrhythmias, and valve disorders.
Cardiac Condition Classification
We categorize cardiac conditions by pathophysiology (heart failure, coronary artery disease, arrhythmias, valvular, cardiomyopathy, vascular) because treatment strategies, monitoring needs, and prognosis differ fundamentally between these categories.
AHA/ACC Clinical Practice Guidelines
Joint American Heart Association/American College of Cardiology guidelines that define standard-of-care for each cardiac condition category.
European Society of Cardiology — Guidelines
ESC clinical practice guidelines providing additional evidence-based recommendations for cardiac care.
CDC Heart Disease Facts
Prevalence and mortality data that informed our cardiac condition prioritization.
Heart Failure Classification — NYHA & ACC/AHA Stages
We use both the NYHA functional classification (I–IV, based on symptoms) and ACC/AHA stages (A–D, based on disease progression) because they serve different purposes: NYHA guides daily management while ACC/AHA stages guide long-term treatment escalation.
Cardiac Medications & Device Therapy
Cardiac treatment combines pharmacotherapy (ACE inhibitors, beta-blockers, anticoagulants, statins) with device-based interventions (pacemakers, ICDs, stents). We track both because each shapes future treatment options and monitoring requirements.
Cardiac Biomarkers & Risk Scores
Cardiac biomarkers (BNP/NT-proBNP, troponin, lipid panels) and risk calculators (ASCVD, CHA₂DS₂-VASc, HEART score) are critical for assessing severity and guiding treatment intensity.
ACC/AHA ASCVD Risk Calculator
Pooled cohort equations for 10-year cardiovascular risk assessment. Informed our risk factor collection.
ACC Biomarker Guidelines for Heart Failure
Guidelines for using natriuretic peptides and troponin in clinical decision-making.
American Heart Association — Understanding Blood Pressure
Blood pressure classification that informed our vital signs tracking.
Neurological Conditions
Parkinson's, Alzheimer's, epilepsy, ALS, and other neurological conditions.
Neurological Condition Classification
We categorize neurological conditions by pathological mechanism (neurodegenerative, demyelinating, seizure, neuromuscular, movement, cerebrovascular) because treatment goals shift from cure to management to neuroprotection depending on the category.
American Academy of Neurology — Practice Guidelines
Evidence-based guidelines for neurological conditions that defined our condition categories and assessment criteria.
National Institute of Neurological Disorders and Stroke (NINDS)
NIH resource covering 600+ neurological conditions. Informed our classification hierarchy and patient-facing descriptions.
WHO Neurological Disorders Report
Global burden of neurological disease data that informed our condition prioritization.
Neurological Assessment & Functional Scales
Neurological severity is measured through validated functional scales specific to each condition (EDSS for MS, Hoehn & Yahr for Parkinson's, MoCA for cognitive decline). We capture functional status because it drives treatment timing and goals.
EDSS — Expanded Disability Status Scale (Multiple Sclerosis)
Standard MS disability measure. Informed our approach to progressive neurological severity assessment.
MDS-UPDRS — Movement Disorder Society Unified Parkinson's Rating Scale
Gold standard Parkinson's assessment tool. Shaped our motor symptom tracking approach.
Montreal Cognitive Assessment (MoCA)
Widely used cognitive screening tool. Informed our cognitive function assessment fields.
Neurological Therapeutics
Neurological treatments span disease-modifying therapies (DMTs for MS), symptomatic management (dopaminergic therapy for Parkinson's), seizure control (anti-epileptic drugs), and emerging neuroprotective strategies. Treatment history is critical because many neurological medications have narrow therapeutic windows and significant interactions.
AAN Treatment Guidelines by Condition
Condition-specific treatment recommendations that informed our medication categories and sequencing.
National MS Society — Disease-Modifying Therapies
Comprehensive DMT reference for MS that informed our treatment tracking for demyelinating conditions.
Epilepsy Foundation — Treatment Options
Anti-seizure medication reference informing our epilepsy-specific treatment fields.
Diabetes & Metabolic
Type 1, Type 2, gestational diabetes, and related metabolic conditions.
Diabetes Classification
We distinguish Type 1, Type 2, gestational, LADA, and MODY because each has fundamentally different pathophysiology, treatment approaches, and monitoring needs. Type 1 requires insulin from diagnosis; Type 2 follows a step-up approach from lifestyle to oral agents to insulin.
ADA Standards of Care in Diabetes (2025)
The definitive annual guidelines for diabetes classification, diagnosis, and management. Our primary reference for all diabetes-related fields.
CDC National Diabetes Statistics Report
Prevalence data and demographic trends that informed our diabetes type categorization.
NIDDK — National Institute of Diabetes and Digestive and Kidney Diseases
NIH diabetes resource covering all types. Informed our patient-facing descriptions and risk factor questions.
Glycemic Control & Monitoring
HbA1c remains the gold standard for long-term glycemic assessment, but we also capture fasting glucose, time-in-range (for CGM users), and hypoglycemia frequency because a complete glycemic picture drives treatment optimization.
ADA Glycemic Targets Guidelines
Target HbA1c, time-in-range goals, and individualized glycemic targets that inform our severity assessment.
International Consensus on Time in Range (2019)
Consensus guidelines for CGM-based time-in-range targets. Informed our CGM data fields.
AACE/ACE Comprehensive Diabetes Management Algorithm
Endocrinology society treatment algorithm used to structure our medication step-up tracking.
Diabetes Medications & Insulin Therapy
We track medication classes (metformin, SGLT2 inhibitors, GLP-1 receptor agonists, insulin) rather than just drug names because class-level information drives treatment sequencing and identifies which pharmacological pathways have been tried.
Complication Screening
Diabetes complications (retinopathy, nephropathy, neuropathy, cardiovascular) are the primary drivers of morbidity. We ask about screening history and existing complications because they shift treatment priorities toward organ protection.
ADA Microvascular Complications Guidelines
Screening intervals and management for retinopathy, nephropathy, and neuropathy.
KDIGO Guidelines — Diabetes & CKD
Kidney Disease: Improving Global Outcomes guidelines for diabetic kidney disease management.
ADA Cardiovascular Risk Management
Guidelines for cardiovascular risk reduction in diabetes, including statin and blood pressure targets.
Rare Diseases
Orphan diseases, undiagnosed conditions, and ultra-rare disorders.
Rare Disease Classification
With 7,000+ known rare diseases, our intake focuses on the diagnostic journey itself — how long diagnosis took, how many specialists were seen, and whether a genetic diagnosis exists. This approach acknowledges that many rare disease patients arrive without a clear treatment pathway.
NIH National Center for Advancing Translational Sciences (NCATS) — Rare Diseases
NIH rare disease research hub. Informed our approach to undiagnosed and ultra-rare conditions.
NORD — National Organization for Rare Disorders
Comprehensive rare disease database and patient advocacy resource. Informed our condition categorization and support resource recommendations.
Orphanet — Portal for Rare Diseases
European rare disease database with classification, prevalence, and treatment data for 6,000+ conditions.
Diagnostic Odyssey
The average rare disease patient waits 5-7 years for diagnosis, seeing 7+ specialists. We capture the diagnostic timeline because it reveals the patient's journey and helps identify gaps in care or missed diagnoses.
Global Genes — RARE Disease Facts
Patient-reported diagnostic journey data. Informed our diagnostic timeline questions.
NIH Undiagnosed Diseases Program (UDP)
NIH program for undiagnosed patients. Shaped our approach to conditions without confirmed diagnoses.
EveryLife Foundation — Rare Disease Impact Report
Data on rare disease economic and quality-of-life burden that informed our functional impact assessment.
Orphan Drug Therapies & Clinical Trials
Only ~5% of rare diseases have FDA-approved treatments. We emphasize clinical trial matching and off-label therapy tracking because for most rare disease patients, trials and compassionate use may be the primary treatment pathways.
FDA Orphan Drug Designations Database
Database of orphan drug designations and approvals. Used to identify available treatments for rare conditions.
ClinicalTrials.gov — Rare Disease Trials
Primary clinical trial registry. We direct rare disease patients here for trial matching.
Genetic and Rare Diseases Information Center (GARD)
NIH information center providing condition-specific treatment and research information for rare diseases.
Our Methodology
Carify's questionnaires are designed to capture the minimum information needed to generate a meaningful, personalized treatment analysis. We prioritize fields that directly influence treatment decisions — every question exists because the answer changes what our AI recommends. We regularly review and update our sources as guidelines evolve.