Richard D Neal

Diagnostic tests for ovarian cancer in premenopausal women with non-specific symptoms (ROCkeTS): prospective, multicentre, cohort study

Abstract Objective To investigate the accuracy of risk prediction models and scores for diagnosing ovarian cancer in premenopausal women presenting to secondary care with symptoms and abnormal test results. Design Prospective cohort study. Setting Secondary care in 23 hospitals in the UK between June 2015 and March 2023. Participants Premenopausal women presenting with non-specific symptoms, and raised serum levels of cancer antigen 125 or abnormal imaging results, were prospectively recruited, predominantly referred through the NHS urgent suspected cancer pathway from primary care. A head-to-head comparison of the accuracy of the six risk prediction models and scores was conducted using donated blood and ultrasound scans performed by NHS staff trained in the use of International Ovarian Tumour Analysis (IOTA) imaging terminology. The index tests used were Risk of Malignancy Index 1 (with pre-stated thresholds of 200, 250), Risk of Malignancy Algorithm (7.4%, 11.4%, 12.5%, 13.1%), IOTA Assessment of Different Neoplasias in the adnEXa (ADNEX) (3%, 10%), IOTA simple rules risk model (3%, 10%), IOTA simple rules, and cancer antigen 125 (CA 125, 87 IU/mL). Participants were classified as having primary invasive ovarian cancer versus having benign or normal pathology according to the reference standard determined from surgical specimens or biopsies by histology or cytology, if undertaken, or else at 12 month follow-up. After June 2018, because of covid restrictions and concerns about sample size, recruitment was restricted to only women undergoing surgery within three months of presentation to clinic (in whom ovarian cancer was more likely). Main outcome measures Diagnostic accuracy at predicting primary invasive ovarian cancer versus benign or normal histology, assessed by analysing the sensitivity, specificity, C index, area under receiver operating characteristic curve, positive and negative predictive values, and calibration plots in participants with conclusive reference standard results and available index test data. Results 88 of 1211 premenopausal women received diagnoses of primary ovarian cancer: 49 of 857 women in the pre-June 2018 cohort (prevalence of 5.7%) and 39 of 354 women in the post-June 2018 cohort (11.0%). For the diagnosis of primary ovarian cancer (n=799 women, after exclusion of 58 other diagnoses), Risk of Malignancy Index 1 at the 250 threshold had a sensitivity of 42.6% (95% confidence interval (CI) 28.3 to 57.8; specificity 96.5%, 94.7 to 97.8). Compared with Risk of Malignancy Index 1 at the 250 threshold, CA 125 and all other tests had higher sensitivity (CA 125 at 87 IU/mL threshold: 55.1%, 40.2 to 69.3, P=0.06; Risk of Malignancy Algorithm at 11.4% threshold: 79.2%, 65.0 to 89.5, P<0.001; IOTA ADNEX at 10% threshold: 89.1%, 76.4 to 96.4, P<0.001; IOTA simple rules risk at 10% threshold: 83.0%, 69.2 to 92.4, P<0.001; IOTA simple rules: 75.0%, 56.6 to 88.5, P=0.01) and lower specificity (CA 125 at 87 IU/mL threshold: 89.0%, 86.5 to 91.2, P<0.001; Risk of Malignancy Algorithm at 11.4% threshold: 73.1%, 69.6 to 76.3, P<0.001; IOTA ADNEX at 10% threshold: 75.1%, 71.4 to 78.6, P<0.001; IOTA simple rules risk at 10% threshold: 76.0%, 72.4 to 79.3, P<0.001; IOTA simple rules: 95.2%, 93.0 to 96.9, P=0.06). Results for IOTA simple rules were inconclusive in 120 of 799 participants. Analysis of the complete cohort (n=1211), including the 354 premenopausal women with a higher likelihood of developing ovarian cancer, yielded similar results. Conclusions Compared to Risk of Malignancy Index 1 at 250 threshold—the test currently used in NHS secondary care to triage women to tertiary care—most tests improve sensitivity but reduce specificity. Ultrasound triage with the IOTA ADNEX model at 10% in secondary care demonstrated the highest sensitivity gain, with a comparable decline in specificity to other comparator tests. Ultrasound with the IOTA ADNEX model at 10% should be considered the new standard of care test for triaging premenopausal women in secondary care. Implementation should incorporate staff training and quality assurance. Trial registration ISRCTN17160843 .

Understanding ethnic inequalities in cancer diagnostic intervals: a cohort study of patients presenting suspected cancer symptoms to GPs in England

BackgroundUK Asian and Black patients experience longer cancer diagnostic intervals — the period between initial symptomatic presentation in primary care and cancer diagnosis.AimTo determine whether the differences in diagnostic intervals are because of prolonged primary care, referral, or secondary care interval.Design and settingA cohort study was undertaken of 70 971 patients with seven cancers (breast, lung, prostate, colorectal, oesophagogastric, myeloma, ovarian) diagnosed after symptom presentation in English primary care.MethodData on symptom presentation and diagnosis were extracted from cancer registry-linked primary care and secondary care data. Primary interval was defined as the period between first primary care presentation and secondary care referral, referral interval as the period between referral and first secondary care appointment, and secondary care interval as the period between the first secondary care appointment and diagnosis. Accelerated failure time models were used to investigate ethnic differences across all four intervals.ResultsAcross all sites, the median diagnostic interval was 46 days, ranging from 13 days for breast cancer to 116 days for lung cancer. It was 14% longer for Black patients (adjusted time ratio [ATR] 1.14, 95% confidence interval [CI] = 1.05 to 1.25) and 13% longer for Asian patients (ATR 1.13, 95% CI = 1.03 to 1.23) compared with White patients. Site-specific analyses showed that, for myeloma, lung, prostate, and colorectal cancer, the secondary care interval was longer in Asian and Black patients, who also had a longer primary care interval in breast and colorectal cancer. There was little evidence of ethnic differences in referral interval.ConclusionThis study found evidence of ethnic differences in diagnostic intervals, with prolonged secondary care intervals for four common cancers and prolonged primary care intervals for two. Although these differences are relatively modest, they are unjustified and may indicate shortcomings in healthcare delivery that disproportionately affect ethnic minorities.