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"""Tests for the Prostate Cancer Mortality prediction model.
Web calculator available at: https://prostate.predict.cam/tool
NOTE: This implementation is based on the Stata reference code from the published
model. There are discrepancies with the current web calculator, particularly for
cases with comorbidities (charlson=1), suggesting the web calculator may use an
updated version or different calibration. Our implementation matches the Stata
code exactly.
"""
import pytest
from sentinel.risk_models.prostate_mortality import ProstateMortalityRiskModel
from sentinel.user_input import (
Anthropometrics,
ClinicalTests,
Demographics,
Ethnicity,
Lifestyle,
PersonalMedicalHistory,
ProstateCancerTreatment,
PSATest,
Sex,
SmokingHistory,
SmokingStatus,
UserInput,
)
def create_test_user(
age: int,
psa: float,
grade_group: int,
t_stage: int,
charlson: int = 0,
treatment: ProstateCancerTreatment = ProstateCancerTreatment.CONSERVATIVE,
ethnicity: Ethnicity = Ethnicity.WHITE,
) -> UserInput:
"""Create a test user with specified prostate cancer parameters.
Args:
age: Patient age in years.
psa: PSA value in ng/mL.
grade_group: Histological grade group (1-5).
t_stage: Clinical T stage (1-4).
charlson: Charlson comorbidity score (0-1).
treatment: Primary treatment received.
ethnicity: Patient ethnicity.
Returns:
UserInput instance configured for prostate mortality testing.
"""
return UserInput(
demographics=Demographics(
age_years=age,
sex=Sex.MALE,
ethnicity=ethnicity,
anthropometrics=Anthropometrics(height_cm=175.0, weight_kg=80.0),
),
lifestyle=Lifestyle(
smoking=SmokingHistory(status=SmokingStatus.NEVER, pack_years=0.0),
),
personal_medical_history=PersonalMedicalHistory(
prostate_cancer_grade_group=grade_group,
prostate_cancer_t_stage=t_stage,
charlson_comorbidity_score=charlson,
prostate_cancer_treatment=treatment,
),
family_history=[],
clinical_tests=ClinicalTests(
psa=PSATest(value_ng_ml=psa),
),
)
GROUND_TRUTH_CASES = [
{
"name": "low_risk_young",
"age": 55,
"psa": 5.0,
"grade_group": 1,
"t_stage": 1,
"charlson": 0,
"treatment": ProstateCancerTreatment.CONSERVATIVE,
"expected_pcsm_15yr": 7.0,
"expected_npcm_15yr": 8.0,
"expected_overall_15yr": 15.0,
},
{
"name": "medium_risk_example",
"age": 65,
"psa": 11.0,
"grade_group": 4,
"t_stage": 2,
"charlson": 0,
"treatment": ProstateCancerTreatment.CONSERVATIVE,
"expected_pcsm_15yr": 19.0,
"expected_npcm_15yr": 26.0,
"expected_overall_15yr": 45.0,
},
{
"name": "moderate_risk",
"age": 60,
"psa": 8.0,
"grade_group": 3,
"t_stage": 2,
"charlson": 0,
"treatment": ProstateCancerTreatment.CONSERVATIVE,
"expected_pcsm_15yr": 15.0,
"expected_npcm_15yr": 15.0,
"expected_overall_15yr": 30.0,
},
]
class TestProstateMortalityRiskModel:
"""Test suite for ProstateMortalityRiskModel."""
def setup_method(self) -> None:
"""Set up test fixtures."""
self.model = ProstateMortalityRiskModel()
def test_metadata(self) -> None:
"""Test model metadata including name, cancer type, and references."""
assert self.model.name == "prostate_mortality"
assert self.model.cancer_type() == "prostate"
assert "Predict Prostate" in self.model.description()
assert "PCSM" in self.model.description()
assert "mortality" in self.model.interpretation().lower()
assert len(self.model.references()) > 0
assert any("predict" in ref.lower() for ref in self.model.references())
def test_absolute_risk_basic(self) -> None:
"""Test basic absolute risk calculation returns valid percentages."""
user = UserInput(
demographics=Demographics(
age_years=65,
sex=Sex.MALE,
ethnicity=Ethnicity.WHITE,
anthropometrics=Anthropometrics(height_cm=175.0, weight_kg=80.0),
),
lifestyle=Lifestyle(
smoking=SmokingHistory(status=SmokingStatus.NEVER, pack_years=0.0),
),
personal_medical_history=PersonalMedicalHistory(
prostate_cancer_grade_group=2,
prostate_cancer_t_stage=1,
charlson_comorbidity_score=0,
),
family_history=[],
clinical_tests=ClinicalTests(
psa=PSATest(value_ng_ml=5.0),
),
)
risks = self.model.absolute_risk(user, years=15)
assert risks["pcsm"] > 0
assert risks["npcm"] > 0
assert risks["overall"] > 0
assert risks["pcsm"] < 100
assert risks["npcm"] < 100
assert risks["overall"] <= 100
@pytest.mark.parametrize("case", GROUND_TRUTH_CASES, ids=lambda case: case["name"])
def test_ground_truth_cases(self, case) -> None:
"""Test model predictions against validated web calculator results.
Args:
case: Test case dictionary with patient parameters and expected results.
"""
if case["expected_pcsm_15yr"] is None:
pytest.skip("TODO: Fill in expected values from web calculator")
user = create_test_user(
age=case["age"],
psa=case["psa"],
grade_group=case["grade_group"],
t_stage=case["t_stage"],
charlson=case["charlson"],
treatment=case["treatment"],
ethnicity=case.get("ethnicity", Ethnicity.WHITE),
)
risks = self.model.absolute_risk(user, years=15)
assert risks["pcsm"] == pytest.approx(case["expected_pcsm_15yr"], abs=4.0)
assert risks["npcm"] == pytest.approx(case["expected_npcm_15yr"], abs=4.0)
assert risks["overall"] == pytest.approx(case["expected_overall_15yr"], abs=4.0)
def test_compute_score_with_male_user_input(self) -> None:
"""Test compute_score returns formatted string for valid male user."""
user = UserInput(
demographics=Demographics(
age_years=65,
sex=Sex.MALE,
ethnicity=Ethnicity.WHITE,
anthropometrics=Anthropometrics(height_cm=175.0, weight_kg=80.0),
),
lifestyle=Lifestyle(
smoking=SmokingHistory(status=SmokingStatus.NEVER, pack_years=0.0),
),
personal_medical_history=PersonalMedicalHistory(
prostate_cancer_grade_group=2,
prostate_cancer_t_stage=1,
charlson_comorbidity_score=0,
prostate_cancer_treatment=ProstateCancerTreatment.CONSERVATIVE,
),
family_history=[],
clinical_tests=ClinicalTests(
psa=PSATest(value_ng_ml=5.0),
),
)
score = self.model.compute_score(user)
assert "PCSM" in score
assert "NPCM" in score
assert "Overall" in score
assert "%" in score
def test_compute_score_rejects_female_user(self) -> None:
"""Test model correctly rejects female patients."""
user = UserInput(
demographics=Demographics(
age_years=65,
sex=Sex.FEMALE,
ethnicity=Ethnicity.WHITE,
anthropometrics=Anthropometrics(height_cm=165.0, weight_kg=70.0),
),
lifestyle=Lifestyle(
smoking=SmokingHistory(status=SmokingStatus.NEVER, pack_years=0.0),
),
personal_medical_history=PersonalMedicalHistory(
prostate_cancer_grade_group=2,
prostate_cancer_t_stage=1,
),
family_history=[],
clinical_tests=ClinicalTests(
psa=PSATest(value_ng_ml=5.0),
),
)
score = self.model.compute_score(user)
assert "N/A" in score
assert "male" in score.lower()
def test_validation_errors(self) -> None:
"""Test validation errors for missing required fields."""
user = UserInput(
demographics=Demographics(
age_years=65,
sex=Sex.MALE,
ethnicity=Ethnicity.WHITE,
anthropometrics=Anthropometrics(height_cm=175.0, weight_kg=80.0),
),
lifestyle=Lifestyle(
smoking=SmokingHistory(status=SmokingStatus.NEVER, pack_years=0.0),
),
personal_medical_history=PersonalMedicalHistory(),
family_history=[],
clinical_tests=ClinicalTests(),
)
score = self.model.compute_score(user)
assert "N/A" in score
assert "Invalid" in score
def test_age_out_of_range(self) -> None:
"""Test age outside validated range raises error."""
user = UserInput(
demographics=Demographics(
age_years=30,
sex=Sex.MALE,
ethnicity=Ethnicity.WHITE,
anthropometrics=Anthropometrics(height_cm=175.0, weight_kg=80.0),
),
lifestyle=Lifestyle(
smoking=SmokingHistory(status=SmokingStatus.NEVER, pack_years=0.0),
),
personal_medical_history=PersonalMedicalHistory(
prostate_cancer_grade_group=2,
prostate_cancer_t_stage=1,
),
family_history=[],
clinical_tests=ClinicalTests(
psa=PSATest(value_ng_ml=5.0),
),
)
score = self.model.compute_score(user)
assert "N/A" in score
def test_psa_validation(self) -> None:
"""Test PSA value validation at boundary values."""
user = UserInput(
demographics=Demographics(
age_years=65,
sex=Sex.MALE,
ethnicity=Ethnicity.WHITE,
anthropometrics=Anthropometrics(height_cm=175.0, weight_kg=80.0),
),
lifestyle=Lifestyle(
smoking=SmokingHistory(status=SmokingStatus.NEVER, pack_years=0.0),
),
personal_medical_history=PersonalMedicalHistory(
prostate_cancer_grade_group=2,
prostate_cancer_t_stage=1,
),
family_history=[],
clinical_tests=ClinicalTests(),
)
score = self.model.compute_score(user)
assert "N/A" in score
def test_competing_risks_consistency(self) -> None:
"""Test competing risks sum correctly to overall mortality."""
user = UserInput(
demographics=Demographics(
age_years=65,
sex=Sex.MALE,
ethnicity=Ethnicity.WHITE,
anthropometrics=Anthropometrics(height_cm=175.0, weight_kg=80.0),
),
lifestyle=Lifestyle(
smoking=SmokingHistory(status=SmokingStatus.NEVER, pack_years=0.0),
),
personal_medical_history=PersonalMedicalHistory(
prostate_cancer_grade_group=3,
prostate_cancer_t_stage=2,
charlson_comorbidity_score=1,
),
family_history=[],
clinical_tests=ClinicalTests(
psa=PSATest(value_ng_ml=10.0),
),
)
risks = self.model.absolute_risk(user, years=15)
total = risks["pcsm"] + risks["npcm"]
assert total == pytest.approx(risks["overall"], abs=0.5)
def test_different_time_horizons(self) -> None:
"""Test model predictions for different time horizons."""
user = UserInput(
demographics=Demographics(
age_years=65,
sex=Sex.MALE,
ethnicity=Ethnicity.WHITE,
anthropometrics=Anthropometrics(height_cm=175.0, weight_kg=80.0),
),
lifestyle=Lifestyle(
smoking=SmokingHistory(status=SmokingStatus.NEVER, pack_years=0.0),
),
personal_medical_history=PersonalMedicalHistory(
prostate_cancer_grade_group=2,
prostate_cancer_t_stage=1,
),
family_history=[],
clinical_tests=ClinicalTests(
psa=PSATest(value_ng_ml=5.0),
),
)
risk_5yr = self.model.absolute_risk(user, years=5)
risk_10yr = self.model.absolute_risk(user, years=10)
risk_15yr = self.model.absolute_risk(user, years=15)
assert risk_5yr["pcsm"] < risk_10yr["pcsm"] < risk_15yr["pcsm"]
assert risk_5yr["npcm"] < risk_10yr["npcm"] < risk_15yr["npcm"]
assert risk_5yr["overall"] < risk_10yr["overall"] < risk_15yr["overall"]
def test_treatment_effect_radical_vs_conservative(self) -> None:
"""Test radical treatment reduces PCSM compared to conservative treatment."""
base_input = {
"demographics": Demographics(
age_years=65,
sex=Sex.MALE,
ethnicity=Ethnicity.WHITE,
anthropometrics=Anthropometrics(height_cm=175.0, weight_kg=80.0),
),
"lifestyle": Lifestyle(
smoking=SmokingHistory(status=SmokingStatus.NEVER, pack_years=0.0),
),
"family_history": [],
"clinical_tests": ClinicalTests(
psa=PSATest(value_ng_ml=10.0),
),
}
user_conservative = UserInput(
**base_input,
personal_medical_history=PersonalMedicalHistory(
prostate_cancer_grade_group=3,
prostate_cancer_t_stage=2,
charlson_comorbidity_score=0,
prostate_cancer_treatment=ProstateCancerTreatment.CONSERVATIVE,
),
)
user_radical = UserInput(
**base_input,
personal_medical_history=PersonalMedicalHistory(
prostate_cancer_grade_group=3,
prostate_cancer_t_stage=2,
charlson_comorbidity_score=0,
prostate_cancer_treatment=ProstateCancerTreatment.RADICAL,
),
)
risk_conservative = self.model.absolute_risk(user_conservative, years=15)
risk_radical = self.model.absolute_risk(user_radical, years=15)
assert risk_radical["pcsm"] < risk_conservative["pcsm"]
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