'If not TB, what could it be?' Chest X-ray findings from the 2016 Kenya Tuberculosis Prevalence Survey.

BACKGROUND: The prevalence of diseases other than TB detected during chest X-ray (CXR) screening is unknown in sub-Saharan Africa. This represents a missed opportunity for identification and treatment of potentially significant disease. Our aim was to describe and quantify non-TB abnormalities identified by TB-focused CXR screening during the 2016 Kenya National TB Prevalence Survey. METHODS: We reviewed a random sample of 1140 adult (≥15 years) CXRs classified as 'abnormal, suggestive of TB' or 'abnormal other' during field interpretation from the TB prevalence survey. Each image was read (blinded to field classification and study radiologist read) by two expert radiologists, with images classified into one of four major anatomical categories and primary radiological findings. A third reader resolved discrepancies. Prevalence and 95% CIs of abnormalities diagnosis were estimated. FINDINGS: Cardiomegaly was the most common non-TB abnormality at 259 out of 1123 (23.1%, 95% CI 20.6% to 25.6%), while cardiomegaly with features of cardiac failure occurred in 17 out of 1123 (1.5%, 95% CI 0.9% to 2.4%). We also identified chronic pulmonary pathology including suspected COPD in 3.2% (95% CI 2.3% to 4.4%) and non-specific patterns in 4.6% (95% CI 3.5% to 6.0%). Prevalence of active-TB and severe post-TB lung changes was 3.6% (95% CI 2.6% to 4.8%) and 1.4% (95% CI 0.8% to 2.3%), respectively. INTERPRETATION: Based on radiological findings, we identified a wide variety of non-TB abnormalities during population-based TB screening. TB prevalence surveys and active case finding activities using mass CXR offer an opportunity to integrate disease screening efforts. FUNDING: National Institute for Health Research (IMPALA-grant reference 16/136/35).

Prevalence, patterns, and factors associated with tobacco use among patients with priority tobacco related illnesses at four Kenyan national referral hospitals, 2022.

Tobacco use is a risk factor for many chronic health conditions. Quantifying burden of tobacco use among people with tobacco-related illnesses (TRI) can strengthen cessation programs. This study estimated prevalence, patterns and correlates of tobacco use among patients with TRI at four national referral hospitals in Kenya. We conducted a cross-sectional study among patients with five TRI (cancer, cardiovascular diseases, cerebrovascular disease, chronic obstructive pulmonary disease, and pulmonary tuberculosis) during January-July 2022. Cases identified from medical records were interviewed on socio-demographic, tobacco use and cessation information. Descriptive statistics were used to characterize patterns of tobacco use. Multiple logistic regression models were used to identify associations with tobacco use. We identified 2,032 individuals with TRI; 46% (939/2,032) had age ≥60 years, and 61% (1,241/2,032) were male. About 45% (923/2,032) were ever tobacco users (6% percent current and 39% former tobacco users). Approximately half of smokers and 58% of smokeless tobacco users had attempted quitting in the last month; 42% through cessation counselling. Comorbidities were present in 28% of the participants. Most (92%) of the patients had been diagnosed with TRI within the previous five years. The most frequent TRI were oral pharyngeal cancer (36% [725/2,032]), nasopharyngeal cancer (12% [246/2.032]) and lung cancer (10% [202/2,032]). Patients >60 years (aOR 2.24, 95% CI: 1.84, 2.73) and unmarried (aOR 1.21, 95% CI: 1.03, 1.42) had higher odds of tobacco use. Female patients (aOR 0.35, 95% CI: 0.30, 0.41) and those with no history of alcohol use (aOR 0.27, 95% CI: 0.23, 0.31), had less odds of tobacco use. Our study shows high prevalence of tobacco use among patients with TRI in Kenya, especially among older, male, less educated, unmarried, and alcohol users. We recommend tobacco use screening and cessation programs among patients with TRI as part of clinical care.

Breast health awareness campaign and screening pilot in a Kenyan County: Findings and lessons.

BACKGROUND AND AIM: Breast cancer is the leading cancer in terms of incidence in Kenya. We conducted a breast cancer awareness and screening pilot to assess feasibility of rolling out a national screening program in Kenya. METHODS: Conducted in Nyeri County during October-November 2019, the pilot had three phases; awareness creation, screening (clinical breast examination and/or imaging) and final evaluation (post-screening exit interviews and retrospective screening data review). Descriptive statistics on awareness, screening process and outputs were derived. RESULTS: During the pilot, 1813 CBE, 217 breast ultrasounds and 600 mammograms were performed. Mammography equipment utilization increased from 11% to 83%. Of 49 women with suspicious lesions on mammography, only 22 (44.9%) had been linked to care 4 months after the campaign. Of 532 exit interview respondents; 95% (505/532) were ≥35 years of age; 80% (426/532) had been reached by the awareness campaign. Majority (75% [399/532]) had received information from community health volunteers; 68% through social groups. Majority (79% [420/532]) felt the campaign had changed their behavior on breast health. Although 77% (407/532) had knowledge on self breast examination (SBE); only 13% practiced monthly SBE. More than half (58% [306/532]) had previously undertaken a CBE. Approximately 70% (375/528) were unaware of mammography before the pilot; 86% (459/532) had never previously undertaken a mammogram. Fifty-five percent (293/532) of respondents had screening waiting times of >120 min. CONCLUSION: Community health workers can create breast cancer screening demand sustainably. Adequate personnel and effective follow-up are crucial before national roll-out of a breast cancer screening program.

Accuracy of computer-aided chest X-ray in community-based tuberculosis screening: Lessons from the 2016 Kenya National Tuberculosis Prevalence Survey.

Community-based screening for tuberculosis (TB) could improve detection but is resource intensive. We set out to evaluate the accuracy of computer-aided TB screening using digital chest X-ray (CXR) to determine if this approach met target product profiles (TPP) for community-based screening. CXR images from participants in the 2016 Kenya National TB Prevalence Survey were evaluated using CAD4TBv6 (Delft Imaging), giving a probabilistic score for pulmonary TB ranging from 0 (low probability) to 99 (high probability). We constructed a Bayesian latent class model to estimate the accuracy of CAD4TBv6 screening compared to bacteriologically-confirmed TB across CAD4TBv6 threshold cut-offs, incorporating data on Clinical Officer CXR interpretation, participant demographics (age, sex, TB symptoms, previous TB history), and sputum results. We compared model-estimated sensitivity and specificity of CAD4TBv6 to optimum and minimum TPPs. Of 63,050 prevalence survey participants, 61,848 (98%) had analysable CXR images, and 8,966 (14.5%) underwent sputum bacteriological testing; 298 had bacteriologically-confirmed pulmonary TB. Median CAD4TBv6 scores for participants with bacteriologically-confirmed TB were significantly higher (72, IQR: 58-82.75) compared to participants with bacteriologically-negative sputum results (49, IQR: 44-57, p<0.0001). CAD4TBv6 met the optimum TPP; with the threshold set to achieve a mean sensitivity of 95% (optimum TPP), specificity was 83.3%, (95% credible interval [CrI]: 83.0%-83.7%, CAD4TBv6 threshold: 55). There was considerable variation in accuracy by participant characteristics, with older individuals and those with previous TB having lowest specificity. CAD4TBv6 met the optimal TPP for TB community screening. To optimise screening accuracy and efficiency of confirmatory sputum testing, we recommend that an adaptive approach to threshold setting is adopted based on participant characteristics.

Kenya tuberculosis prevalence survey 2016: Challenges and opportunities of ending TB in Kenya.

BACKGROUND: We aimed to determine the prevalence of pulmonary TB amongst the adult population (≥15 years) in 2016 in Kenya. METHOD: A nationwide cross-sectional survey where participants first underwent TB symptom screening and chest x-ray. Subsequently, participants who reported cough >2weeks and/or had a chest x-ray suggestive of TB, submitted sputum specimen for laboratory examination by smear microscopy, culture and Xpert MTB/RIF. RESULT: The survey identified 305 prevalent TB cases translating to a prevalence of 558 [95%CI 455-662] per 100,000 adult population. The highest disease burden was reported among people aged 25-34 years (716 [95% CI 526-906]), males (809 [(95% CI 656-962]) and those who live in urban areas (760 [95% CI 539-981]). Compared to the reported TB notification rate for Kenya in 2016, the prevalence to notification ratio was 2.5:1. The gap between the survey prevalence and notification rates was highest among males, age groups 25-34, and the older age group of 65 years and above. Only 48% of the of the survey prevalent cases reported cough >2weeks. In addition, only 59% of the identified cases had the four cardinal symptoms for TB (cough ≥2 weeks, fever, night sweat and weight loss. However, 88.2% had an abnormal chest x-ray suggestive of TB. The use of Xpert MTB/RIF identified 77.7% of the cases compared to smear microscopy's 46%. Twenty-one percent of the survey participants with respiratory symptoms reported to have sought prior health care at private clinics and chemists. Among the survey prevalent cases who reported TB related symptoms, 64.9% had not sought any health care prior to the survey. CONCLUSION: This survey established that TB prevalence in Kenya is higher than had been estimated, and about half of the those who fall ill with the disease each year are missed.