Kinetics of glucose-6-phosphate dehydrogenase (G6PD) activity during Plasmodium vivax infection: implications for early radical malaria treatment.

BACKGROUND: Plasmodium vivax relapses due to dormant liver hypnozoites can be prevented with primaquine. However, the dose must be adjusted in individuals with glucose-6-phosphate-dehydrogenase (G6PD) deficiency. In French Guiana, assessment of G6PD activity is typically delayed until day (D)14 to avoid the risk if misclassification. This study assessed the kinetics of G6PD activity throughout P. vivax infection to inform the timing of treatment. METHODS: For this retrospective monocentric study, data on G6PD activity between D1 and D28 after treatment initiation with chloroquine or artemisinin-based combination therapy were collected for patients followed at Cayenne Hospital, French Guiana, between January 2018 and December 2020. Patients were divided into three groups based on the number of available G6PD activity assessments: (i) at least two measurements during the P. vivax malaria infection; (ii) two measurements: one during the current infection and one previously; (iii) only one measurement during the malaria infection. RESULTS: In total, 210 patients were included (80, 20 and 110 in groups 1, 2 and 3, respectively). Data from group 1 showed that G6PD activity remained stable in each patient over time (D1, D3, D7, D14, D21, D28). None of the patients with normal G6PD activity during the initial phase (D1-D3) of the malaria episode (n = 44) was categorized as G6PD-deficient at D14. Patients with G6PD activity < 80% at D1 or D3 showed normal activity at D14. Sex and reticulocyte count were statistically associated with G6PD activity variation. In the whole sample (n = 210), no patient had severe G6PD deficiency (< 10%) and only three between 10 and 30%, giving a G6PD deficiency prevalence of 1.4%. Among the 100 patients from group 1 and 2, 30 patients (26.5%) were lost to follow-up before primaquine initiation. CONCLUSIONS: In patients treated for P. vivax infection, G6PD activity did not vary over time. Therefore, G6PD activity on D1 instead of D14 could be used for primaquine dose-adjustment. This could allow earlier radical treatment with primaquine, that could have a public health impact by decreasing early recurrences and patients lost to follow-up before primaquine initiation. This hypothesis needs to be confirmed in larger prospective studies.

Evaluation of maternal and child care continuum in Guinea: a secondary analysis of two demographic and health surveys using the composite coverage index (CCI).

INTRODUCTION: The composite coverage index (CCI) is the weighted average coverage of eight preventive and curative interventions received along the maternal and childcare continuum. This study aimed to analyse maternal and child health indicators using CCI. METHODS: We performed a secondary analysis of demographic and health surveys (DHS) focused on women aged 15 to 49 and their children aged 1 to 4. This study took place in Guinea. The CCI (meeting the need for planning, childbirth assisted by qualified healthcare workers, antenatal care assisted by qualified healthcare workers, vaccination against diphtheria, pertussis, tetanus, measles and Bacillus Calmette-Guérin, taking oral rehydration salts during diarrhoea and seeking care for pneumonia) is optimal if the weighted proportion of interventions is > 50%; otherwise, it is partial. We identified the factors associated with CCI using the descriptive association tests, the spatial autocorrelation statistic and multivariate logistic regression. RESULTS: The analyses involved two DHS surveys, with 3034 included in 2012 and 4212 in 2018. The optimal coverage of the CCI has increased from 43% in 2012 to 61% in 2018. In multivariate analysis, in 2012: the poor had a lower probability of having an optimal CCI than the richest; OR = 0.11 [95% CI; 0.07, 0.18]. Those who had done four antenatal care visits (ANC) were 2.78 times more likely to have an optimal CCI than those with less OR = 2.78 [95% CI;2.24, 3.45]. In 2018: the poor had a lower probability of having an optimal CCI than the richest OR = 0.27 [95% CI; 0.19, 0.38]. Women who planned their pregnancies were 28% more likely to have an optimal CCI than those who had not planned OR = 1.28 [95% CI;1.05, 1.56]. Finally, women with more than 4 ANC were 2.43 times more likely to have an optimal CCI than those with the least OR = 2.43 [95% CI; 2.03, 2.90]. The spatial analysis reveals significant disparities with an aggregation of high partial CCI in Labé between 2012 and 2018. CONCLUSION: This study showed an increase in CCI between 2012 and 2018. Policies should improve access to care and information for poor women. Besides, strengthening ANC visits and reducing regional inequalities increases optimal CCI.

A new cure model that corrects for increased risk of non-cancer death: analysis of reliability and robustness, and application to real-life data.

BACKGROUND: Non-cancer mortality in cancer patients may be higher than overall mortality in the general population due to a combination of factors, such as long-term adverse effects of treatments, and genetic, environmental or lifestyle-related factors. If so, conventional indicators may underestimate net survival and cure fraction. Our aim was to propose and evaluate a mixture cure survival model that takes into account the increased risk of non-cancer death for cancer patients. METHODS: We assessed the performance of a corrected mixture cure survival model derived from a conventional mixture cure model to estimate the cure fraction, the survival of uncured patients, and the increased risk of non-cancer death in two settings of net survival estimation, grouped life-table data and individual patients' data. We measured the model's performance in terms of bias, standard deviation of the estimates and coverage rate, using an extensive simulation study. This study included reliability assessments through violation of some of the model's assumptions. We also applied the models to colon cancer data from the FRANCIM network. RESULTS: When the assumptions were satisfied, the corrected cure model provided unbiased estimates of parameters expressing the increased risk of non-cancer death, the cure fraction, and net survival in uncured patients. No major difference was found when the model was applied to individual or grouped data. The absolute bias was < 1% for all parameters, while coverage ranged from 89 to 97%. When some of the assumptions were violated, parameter estimates appeared more robust when obtained from grouped than from individual data. As expected, the uncorrected cure model performed poorly and underestimated net survival and cure fractions in the simulation study. When applied to colon cancer real-life data, cure fractions estimated using the proposed model were higher than those in the conventional model, e.g. 5% higher in males at age 60 (57% vs. 52%). CONCLUSIONS: The present analysis supports the use of the corrected mixture cure model, with the inclusion of increased risk of non-cancer death for cancer patients to provide better estimates of indicators based on cancer survival. These are important to public health decision-making; they improve patients' awareness and facilitate their return to normal life.

Correcting for heterogeneity and non-comparability bias in multicenter clinical trials with a rescaled random-effect excess hazard model.

In the presence of competing causes of event occurrence (e.g., death), the interest might not only be in the overall survival but also in the so-called net survival, that is, the hypothetical survival that would be observed if the disease under study were the only possible cause of death. Net survival estimation is commonly based on the excess hazard approach in which the hazard rate of individuals is assumed to be the sum of a disease-specific and expected hazard rate, supposed to be correctly approximated by the mortality rates obtained from general population life tables. However, this assumption might not be realistic if the study participants are not comparable with the general population. Also, the hierarchical structure of the data can induces a correlation between the outcomes of individuals coming from the same clusters (e.g., hospital, registry). We proposed an excess hazard model that corrects simultaneously for these two sources of bias, instead of dealing with them independently as before. We assessed the performance of this new model and compared it with three similar models, using extensive simulation study, as well as an application to breast cancer data from a multicenter clinical trial. The new model performed better than the others in terms of bias, root mean square error, and empirical coverage rate. The proposed approach might be useful to account simultaneously for the hierarchical structure of the data and the non-comparability bias in studies such as long-term multicenter clinical trials, when there is interest in the estimation of net survival.

Incidence and Survival in Synchronous and Metachronous Liver Metastases From Colorectal Cancer.

Importance: Although treatment and prognosis of synchronous liver metastases from colorectal cancer are relatively well known, a comparative description of the incidence, epidemiological features, and outcomes of synchronous and metachronous liver metastases is lacking. The difference in prognosis between patients with synchronous and metachronous liver metastases is controversial. Objective: To investigate temporal patterns in the incidence and outcomes of synchronous vs metachronous liver metastases from colorectal cancer. Design, Setting, and Participants: This population-based cohort study used information from a French regional digestive cancer registry accounting for 1 082 000 inhabitants. A total of 26 813 patients with a diagnosis of incident colorectal adenocarcinoma diagnosed between January 1, 1976, and December 31, 2018, were included. Data were analyzed from February 7 to May 20, 2022. Main Outcomes and Measures: Age-standardized incidence was calculated. Univariate and multivariate net survival analyses were performed. Results: Of 26 813 patients with colorectal cancer (15 032 men [56.1%]; median [IQR] age, 73 [64-81] years), 4546 (17.0%) presented with synchronous liver metastases. The incidence rate of synchronous liver metastases was 6.9 per 100 000 inhabitants in men and 3.4 per 100 000 inhabitants in women, with no significant variation since 2000. The 5-year cumulative incidence of metachronous liver metastases decreased from 18.6% (95% CI, 14.9%-22.2%) during the 1976 to 1980 period to 10.0% (95% CI, 8.8%-11.2%) during the 2006 to 2011 period. Cancer stage at diagnosis was the strongest risk factor for liver metastases; compared with patients diagnosed with stage II cancer, patients with stage III cancer had a 2-fold increase in risk (subdistribution hazard ratio, 2.42; 95% CI, 2.08-2.82) for up to 5 years. Net survival at 1 year was 41.8% for synchronous liver metastases and 49.9% for metachronous metastases, and net survival at 5 years was 6.2% for synchronous liver metastases and 13.2% for metachronous metastases. Between the first (1976-1980) and last (2011-2016) periods, the adjusted ratio of death after synchronous and metachronous metastases was divided by 2.5 for patients with synchronous status and 3.7 for patients with metachronous status. Conclusions and Relevance: In this study, the incidence of colorectal cancer with synchronous liver metastases changed little over time, whereas there was a 2-fold decrease in the probability of developing metachronous liver metastases. Survival improved substantially for patients with metachronous liver metastases, whereas improvement was more modest for those with synchronous metastases. The differences observed in the epidemiological features of synchronous and metachronous liver metastases from colorectal cancer may be useful for the design of future clinical trials.

Health status of prevalent cancer cases as measured by mortality dynamics (cancer vs. noncancer): Application to five major cancers sites.

BACKGROUND: Cancer prevalence is heterogeneous because it includes individuals who are undergoing initial treatment and those who are in remission, experiencing relapse, or cured. The proposed statistical approach describes the health status of this group by estimating the probabilities of death among prevalent cases. The application concerns colorectal, lung, breast, and prostate cancers and melanoma in France in 2017. METHODS: Excess mortality was used to estimate the probabilities of death from cancer and other causes. RESULTS: For the studied cancers, most deaths from cancer occurred during the first 5 years after diagnosis. The probability of death from cancer decreased with increasing time since diagnosis except for breast cancer, for which it remained relatively stable. The time beyond which the probability of death from cancer became lower than that from other causes depended on age and cancer site: for colorectal cancer, it was 6 years after diagnosis for women (7 years for men) aged 75-84 and 20 years for women (18 years for men) aged 45-54 years, whereas cancer was the major cause of death for women younger than 75 years whatever the time since diagnosis for breast and for all patients younger than 75 years for lung cancer. In contrast, deaths from other causes were more frequent in all the patients older than 75 years. Apart from breast cancer in women younger than 55 years and lung cancer in women older than 55 years and men older than 65 years, the probability of death from cancer among prevalent cases fell below 1%, with varying times since diagnosis. CONCLUSIONS: The authors' approach can be used to better describe the burden of cancer by estimating outcomes in prevalent cases.

Modelling factors associated with therapeutic inertia in hypertensive patients: Analysis using repeated data from a hospital registry in West Africa.

The proportion of poorly controlled hypertensives still remains high in the general African population. This is largely due to therapeutic inertia (TI), defined as the failure to intensify or modify treatment in a patient with poorly controlled blood pressure (BP). The objective of this study was to identify the determinants of TI. We conducted a retrospective cohort study from March 2012 to February 2014 of hypertensive patients followed during 4 medical visits. The TI score was the number of visits with TI divided by the number of visits where a therapeutic change was indicated. A random-effects logistic model was used to identify the determinants of TI. A total of 200 subjects were included, with a mean age of 57.98 years and 67% men. The TI score was measured at 85.57% (confidence interval [CI] 95% = [82.41-88.92]). Measured individual heterogeneity was significantly significant (0.78). Three factors were associated with treatment inertia, namely the number of antihypertensive drugs (odd ratios [OR] = 1.27; CI = [1.02-1.58]), the time between consultations (OR = 0.94; CI = [0.91-0.97]), and treatment noncompliance (OR = 15.18; CI = [3.13-73.70]). The random-effects model performed better in predicting high-risk patients with TI than the classical logistic model (P value < .001). Our study showed a high TI score in patients followed in cardiology in Burkina Faso. Reduction of the TI score through targeted interventions is necessary to better control hypertension in our cohort patients.

Correcting inaccurate background mortality in excess hazard models through breakpoints.

BACKGROUND: Methods for estimating relative survival are widely used in population-based cancer survival studies. These methods are based on splitting the observed (the overall) mortality into excess mortality (due to cancer) and background mortality (due to other causes, as expected in the general population). The latter is derived from life tables usually stratified by age, sex, and calendar year but not by other covariates (such as the deprivation level or the socioeconomic status) which may lack though they would influence background mortality. The absence of these covariates leads to inaccurate background mortality, thus to biases in estimating the excess mortality. These biases may be avoided by adjusting the background mortality for these covariates whenever available. METHODS: In this work, we propose a regression model of excess mortality that corrects for potentially inaccurate background mortality by introducing age-dependent multiplicative parameters through breakpoints, which gives some flexibility. The performance of this model was first assessed with a single and two breakpoints in an intensive simulation study, then the method was applied to French population-based data on colorectal cancer. RESULTS: The proposed model proved to be interesting in the simulations and the applications to real data; it limited the bias in parameter estimates of the excess mortality in several scenarios and improved the results and the generalizability of Touraine's proportional hazards model. CONCLUSION: Finally, the proposed model is a good approach to correct reliably inaccurate background mortality by introducing multiplicative parameters that depend on age and on an additional variable through breakpoints.

Correcting for misclassification and selection effects in estimating net survival in clinical trials.

BACKGROUND: Net survival, a measure of the survival where the patients would only die from the cancer under study, may be compared between treatment groups using either "cause-specific methods", when the causes of death are known and accurate, or "population-based methods", when the causes are missing or inaccurate. The latter methods rely on the assumption that mortality due to other causes than cancer is the same as the expected mortality in the general population with same demographic characteristics derived from population life tables. This assumption may not hold in clinical trials where patients are likely to be quite different from the general population due to some criteria for patient selection. METHODS: In this work, we propose and assess the performance of a new flexible population-based model to estimate long-term net survival in clinical trials and that allows for cause-of-death misclassification and for effects of selection. Comparisons were made with cause-specific and other population-based methods in a simulation study and in an application to prostate cancer clinical trial data. RESULTS: In estimating net survival, cause-specific methods seemed to introduce important biases associated with the degree of misclassification of cancer deaths. The usual population-based method provides also biased estimates, depending on the strength of the selection effect. Compared to these methods, the new model was able to provide more accurate estimates of net survival in long-term clinical trials. CONCLUSION: Finally, the new model paves the way for new methodological developments in the field of net survival methods in multicenter clinical trials.

Impact of socioeconomic inequalities on geographic disparities in cancer incidence: comparison of methods for spatial disease mapping.

BACKGROUND: The reliability of spatial statistics is often put into question because real spatial variations may not be found, especially in heterogeneous areas. Our objective was to compare empirically different cluster detection methods. We assessed their ability to find spatial clusters of cancer cases and evaluated the impact of the socioeconomic status (e.g., the Townsend index) on cancer incidence. METHODS: Moran's I, the empirical Bayes index (EBI), and Potthoff-Whittinghill test were used to investigate the general clustering. The local cluster detection methods were: i) the spatial oblique decision tree (SpODT); ii) the spatial scan statistic of Kulldorff (SaTScan); and, iii) the hierarchical Bayesian spatial modeling (HBSM) in a univariate and multivariate setting. These methods were used with and without introducing the Townsend index of socioeconomic deprivation known to be related to the distribution of cancer incidence. Incidence data stemmed from the Cancer Registry of Isère and were limited to prostate, lung, colon-rectum, and bladder cancers diagnosed between 1999 and 2007 in men only. RESULTS: The study found a spatial heterogeneity (p < 0.01) and an autocorrelation for prostate (EBI = 0.02; p = 0.001), lung (EBI = 0.01; p = 0.019) and bladder (EBI = 0.007; p = 0.05) cancers. After introduction of the Townsend index, SaTScan failed in finding cancers clusters. This introduction changed the results obtained with the other methods. SpODT identified five spatial classes (p < 0.05): four in the Western and one in the Northern parts of the study area (standardized incidence ratios: 1.68, 1.39, 1.14, 1.12, and 1.16, respectively). In the univariate setting, the Bayesian smoothing method found the same clusters as the two other methods (RR >1.2). The multivariate HBSM found a spatial correlation between lung and bladder cancers (r = 0.6). CONCLUSIONS: In spatial analysis of cancer incidence, SpODT and HBSM may be used not only for cluster detection but also for searching for confounding or etiological factors in small areas. Moreover, the multivariate HBSM offers a flexible and meaningful modeling of spatial variations; it shows plausible previously unknown associations between various cancers.