| 1. |
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| 2. |
- Back, Erik, et al.
(författare)
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Permanent stoma rates after anterior resection for rectal cancer : risk prediction scoring using preoperative variables
- 2021
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Ingår i: British Journal of Surgery. - : Oxford University Press. - 0007-1323 .- 1365-2168. ; 108:11, s. 1388-1395
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: A permanent stoma after anterior resection for rectal cancer is common. Preoperative counselling could be improved by providing individualized accurate prediction modelling.METHODS: Patients who underwent anterior resection between 2007 and 2015 were identified from the Swedish Colorectal Cancer Registry. National Patient Registry data were added to determine presence of a stoma 2 years after surgery. A training set based on the years 2007-2013 was employed in an ensemble of prediction models. Judged by the area under the receiving operating characteristic curve (AUROC), data from the years 2014-2015 were used to evaluate the predictive ability of all models. The best performing model was subsequently implemented in typical clinical scenarios and in an online calculator to predict the permanent stoma risk.RESULTS: Patients in the training set (n = 3512) and the test set (n = 1136) had similar permanent stoma rates (13.6 and 15.2 per cent). The logistic regression model with a forward/backward procedure was the most parsimonious among several similarly performing models (AUROC 0.67, 95 per cent c.i. 0.63 to 0.72). Key predictors included co-morbidity, local tumour category, presence of metastasis, neoadjuvant therapy, defunctioning stoma use, tumour height, and hospital volume; the interaction between age and metastasis was also predictive.CONCLUSION: Using routinely available preoperative data, the stoma outcome at 2 years after anterior resection for rectal cancer can be predicted fairly accurately.
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| 3. |
- Barros, Guilherme, 1992-
(författare)
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Estimation of hazard ratios from observational data with applications related to stroke
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The objective of this thesis is to examine some challenges that may emerge when conducting time-to-event studies based on observational data. Time-to-event (also called survival) is a setting that involves analyzing how different factors may influence the length of time until an individual experiences the event of interest. This type of analysis is commonly applied in fields such as medical research and epidemiology. In this thesis, which focuses on stroke, we are interested in the time to a recurrent stroke or the death of a patient who survived a first stroke.Hazard ratios are one of the main parameters estimated in time-to-event studies. Hazard ratios involve comparing the risk of experiencing the event between two groups, usually a treated group and an untreated group. They can also involve other factors, such as different age groups. Hazard ratios can be estimated from the data by using the Cox regression model.Observational data, in contrast to experimental data, involves data collected without any intervention or random assignment of treatment to the individuals. Confounders, that is, variables that distort or obscure the true relationship between treatment and outcome, are always present and need to be controlled for in observational studies.National registers are an important source of observational data. A national registry is a centralized database or system that collects, stores, and maintains information about a specific population or group of individuals within a country. Sweden is known for its detailed and complete national registers. In this thesis, data from the Swedish Stroke Register (Riksstroke) is used to study factors related to stroke.In time-to-event studies involving observational data, several challenges may arise for the researcher during data analysis. Some individuals may not experience the event during the observation period and thus the information about their time until the event is incomplete. These individuals are considered as censored. Some individuals may experience another event rather than the one of interest, a competing risk. Additionally, models must be properly constructed, with researchers selecting variables and determining the suitable functional form.Four papers are included in the thesis. Paper I demonstrates how to handle competing risks in survival analysis. The study involves comparing individuals with and without standard modifiable risk factors and their risks of a recurrent stroke or death using data from the Swedish Stroke Register.The estimation of marginal hazard ratios is a common theme in the other three papers. All involve simulation studies in order to extend methods and explore best practices when estimating marginal hazard ratios.Paper II explores non-parametric methods that can be used as alternatives to more traditional parametric methods when balancing datasets in order to estimate a marginal hazard ratio. A case study was also conducted using data from the Swedish Stroke Register involving the prescription of anticoagulants at hospital discharge after a stroke.Paper III is about how censoring affects marginal hazard ratio estimation, even with perfect balancing of the dataset. We study this issue, taking into consideration varying effect sizes and censoring rates. A procedure to attenuate the problem is also studied.Paper IV concerns covariate selection in the case of high-dimensional data. High-dimensional data involves cases in which the number of covariates in the study is comparable to the number of individuals, and therefore covariate selection methods are needed. In the paper, we explore some of these methods and suggest a best-performing procedure. As Paper II, Paper IV involves a case study of anticoagulant prescription using data from the Swedish Stroke Register.
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| 4. |
- Barros, Guilherme W. F., et al.
(författare)
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Performance of modeling and balancing approach methods when using weights to estimate treatment effects in observational time-to-event settings
- 2023
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 18:12
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Tidskriftsartikel (refereegranskat)abstract
- In observational studies weighting techniques are often used to overcome bias due to confounding. Modeling approaches, such as inverse propensity score weighting, are popular, but often rely on the correct specification of a parametric model wherein neither balance nor stability are targeted. More recently, balancing approach methods that directly target covariate imbalances have been proposed, and these allow the researcher to explicitly set the desired balance constraints. In this study, we evaluate the finite sample properties of different modeling and balancing approach methods, when estimating the marginal hazard ratio, through Monte Carlo simulations. The use of the different methods is also illustrated by analyzing data from the Swedish stroke register to estimate the effect of prescribing oral anticoagulants on time to recurrent stroke or death in stroke patients with atrial fibrillation. In simulated scenarios with good overlap and low or no model misspecification the balancing approach methods performed similarly to the modeling approach methods. In scenarios with bad overlap and model misspecification, the modeling approach method incorporating variable selection performed better than the other methods. The results indicate that it is valuable to use methods that target covariate balance when estimating marginal hazard ratios, but this does not in itself guarantee good performance in situations with, e.g., poor overlap, high censoring, or misspecified models/balance constraints.
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| 5. |
- Boström, Petrus, et al.
(författare)
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Oncological Impact of High Vascular Tie After Surgery for Rectal Cancer : A Nationwide Cohort Study
- 2021
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Ingår i: Annals of Surgery. - : Wolters Kluwer. - 0003-4932 .- 1528-1140. ; 274:3, s. e236-e244
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Tidskriftsartikel (refereegranskat)abstract
- Objective: The purpose of this study was to investigate the impact of tie level on oncological outcomes in rectal cancer surgery.Summary background data: Theoretically, a high tie of the inferior mesenteric artery could facilitate removal of apical node metastases and improve tumor staging accuracy. However, no appropriately sized randomized controlled trial exists and results from observational studies are not consistent.Methods: All stage I–III rectal cancer patients who underwent abdominal surgery with curative intention in 2007 to 2014 were identified and followed, using the Swedish Colorectal Cancer Registry. Primary outcome was cancer-specific survival, whereas overall and relative survival, locoregional and distant recurrence, and lymph node harvest were secondary outcomes, with high tie as exposure. We used propensity score matching to emulate a randomized controlled trial, and then performed Cox regression analyses to estimate hazard ratios (HRs) with confidence intervals (CIs).Results: Some 8287 patients remained for analysis, of which 37% had high tie surgery. After propensity score matching, the 5-year cancer-specific survival rate was overall 86% and we found no association between the level of tie and cancer-specific (HR 0.92, 95% CI 0.79–1.07) or overall (HR 0.98, 95% CI 0.89–1.08) survival, nor to locoregional (HR 0.85, 95% CI 0.59–1.23) or distant (HR 1.01, 95% CI 0.88–1.15) recurrence, nor to relative survival (HR 1.05, 95% CI 0.85–1.28). Stratification and sensitivity analyses were similarly insignificant, after adjustment for confounding. Total lymph node harvest was, however, increased after high tie surgery (P < 0.01), but no differences were seen regarding positive nodes (P = 0.72).Conclusion: In this nationwide cohort study, the level of tie did not influence any patient-oriented oncological outcome, neither overall nor in node-positive patients. This would allow the patient's anatomical configuration and the surgeon's preferences to determine the level of tie.
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| 6. |
- Gerdin, Anders, et al.
(författare)
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Preoperative beta blockers and other drugs in relation to anastomotic leakage after anterior resection for rectal cancer
- 2024
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Ingår i: Colorectal Disease. - : John Wiley & Sons. - 1462-8910 .- 1463-1318. ; 26:5, s. 974-986
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Tidskriftsartikel (refereegranskat)abstract
- Aim: Previous research has indicated that preoperative beta blocker therapy is associated with a decreased risk of complications after surgery for rectal cancer. This is thought to arise because of the anti-inflammatory activity of the drug. These results need to be reproduced and analyses extended to other drugs with such properties, as this information might be useful in clinical decision-making. The main aim of this work was to replicate previous findings of beta blocker use as a prognostic marker for postoperative leakage. We also investigated whether drug exposure might induce anastomotic leaks.Method: This is a retrospective multicentre cohort study, comprising 1126 patients who underwent anterior resection for rectal cancer between 2014 and 2018. The use of any preoperative beta blocker was treated as the primary exposure, while anastomotic leakage within 12 months of surgery was the outcome. Secondary exposures comprised angiotensin-converting enzyme inhibitors/angiotensin receptor blockers, statins and metformin. Using multivariable regression, we performed a replication analysis with a predictive aim for beta blockers only, while adjustment for confounding was done in more causally oriented analyses for all drugs. We estimated incidence rate ratio (IRR) and relative risk (RR) with 95% confidence intervals (CIs).Results: Anastomotic leakage occurred in 20.6% of patients. Preoperative beta blockers were used by 22.7% of the cohort, while the leak distribution was almost identical between exposure groups. In the main replication analysis, no association could be detected (IRR 0.95, 95% CI 0.68–1.33). In the causally oriented analyses, only metformin affected the risk of leakage (RR 1.59, 95% Cl 1.31–1.92).Conclusion: While previous research has suggested that preoperative beta blocker use could be prognostic of anastomotic leakage, this study could not detect any such association. On the contrary, our results indicate that preoperative beta blocker use neither predicts nor causes anastomotic leakage after anterior resection for rectal cancer.
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| 7. |
- Golshani, P., et al.
(författare)
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The modified Glasgow Prognostic Score indicates an increased risk of anastomotic leakage after anterior resection for rectal cancer
- 2023
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Ingår i: International Journal of Colorectal Disease. - : Springer. - 0179-1958 .- 1432-1262. ; 38:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundPreoperative inflammation might cause and also be a marker for anastomotic leakage after anterior resection for rectal cancer. Available biomarker indices such as the modified Glasgow Prognostic Score (mGPS) or the C-reactive protein-to-albumin ratio (CAR) may be clinically useful for leakage assessment.MethodsPatients who underwent anterior resection for rectal cancer during 2014-2018 from a multicentre retrospective cohort were included. Data from the Swedish Colorectal Cancer registry and chart review at each hospital were collected. In a subset of patients, preoperative laboratory assessments were available, constituting the exposures mGPS and CAR. Anastomotic leakage within 12 months was the outcome. Causally oriented analyses were conducted with adjustment for confounding, as well as predictive models.ResultsA total of 418 patients were eligible for analysis. Most patients had mGPS = 0 (84.7%), while mGPS = 1 (10.8%) and mGPS = 2 (4.5%) were less common. mGPS = 2 (OR: 4.11; 95% CI: 1.69-10.03) seemed to confer anastomotic leakage, while this was not seen for mGPS = 1 (OR 1.09; 95% CI: 0.53-2.25). A cut off point of CAR > 0.36 might be indicative of leakage (OR 2.25; 95% CI: 1.21-4.19). Predictive modelling using mGPS rendered an area-under-the-curve of 0.73 (95% CI: 0.67-0.79) at most.DiscussionPreoperative inflammation seems to be involved in the development of anastomotic leakage after anterior resection for cancer. Inclusion into prediction models did not result in accurate leakage prediction, but high degrees of systemic inflammation might still be important in clinical decision-making.
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| 8. |
- Holmgren, Klas, et al.
(författare)
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Defunctioning stomas may reduce chances of a stoma-free outcome after anterior resection for rectal cancer
- 2021
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Ingår i: Colorectal Disease. - : Blackwell Publishing. - 1462-8910 .- 1463-1318. ; 23:11, s. 2859-2869
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Tidskriftsartikel (refereegranskat)abstract
- AIM: To investigate the conflicting consequences of faecal diversion on stoma outcomes and anastomotic leakage in anterior resection for rectal cancer, including interaction effects determined by the extent of mesorectal excision.METHOD: Anterior resections between 2007 and 2016 were identified using the Swedish Colorectal Cancer Registry. National Patient Registry data were added to determine stoma outcome 2 years after surgery. Tumour distance from the anal verge constituted a proxy for extent of mesorectal excision [total mesorectal excision (TME): ≤10 cm; partial mesorectal excision (PME): 13-15 cm]. With confounder-adjusted probit regression, the total effect of defunctioning stoma on permanent stoma, and the interaction effect of extent of mesorectal excision, were estimated together with the indirect effect through anastomotic leakage. Baseline risks, risk differences (RDs) and relative risks (RRs) were reported.RESULTS: The main study cohort included 4529 patients. Defunctioning stomas influenced the absolute permanent stoma risk (TME: RD 0.11 [95% CI 0.09-0.13]; PME: RD 0.15 [95% CI 0.13-0.16]). The baseline risk was higher in TME, with a resulting greater RR in PME (2.23 [95% CI 1.43-3.02] vs 4.36 [95% CI 3.05-5.68]). The indirect reduction in permanent stoma rates, due to the alleviating effect of faecal diversion on anastomotic leakage, was small (TME: 0.89 [95% CI 0.81-0.96]; PME: 0.96 [95% CI 0.91-1.00]).CONCLUSION: In anterior resection for rectal cancer, defunctioning stomas may reduce chances of a stoma-free outcome. Considering leakage reduction benefits, consequences of routine diversion in TME might be fairly balanced, while this seems questionable in PME.
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| 9. |
- Moosavi, Niloofar, et al.
(författare)
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The costs and benefits of uniformly valid causal inference with high-dimensional nuisance parameters
- 2023
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Ingår i: Statistical Science. - : Institute of Mathematical Statistics. - 0883-4237 .- 2168-8745. ; 38:1, s. 1-12
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Tidskriftsartikel (refereegranskat)abstract
- Important advances have recently been achieved in developing procedures yielding uniformly valid inference for a low dimensional causal parameter when high-dimensional nuisance models must be estimated. In this paper, we review the literature on uniformly valid causal inference and discuss the costs and benefits of using uniformly valid inference procedures. Naive estimation strategies based on regularisation, machine learning, or a preliminary model selection stage for the nuisance models have finite sample distributions which are badly approximated by their asymptotic distributions. To solve this serious problem, estimators which converge uniformly in distribution over a class of data generating mechanisms have been proposed in the literature. In order to obtain uniformly valid results in high-dimensional situations, sparsity conditions for the nuisance models need typically to be made, although a double robustness property holds, whereby if one of the nuisance model is more sparse, the other nuisance model is allowed to be less sparse. While uniformly valid inference is a highly desirable property, uniformly valid procedures pay a high price in terms of inflated variability. Our discussion of this dilemma is illustrated by the study of a double-selection outcome regression estimator, which we show is uniformly asymptotically unbiased, but is less variable than uniformly valid estimators in the numerical experiments conducted.
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| 10. |
- Moosavi, Niloofar, 1990-
(författare)
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Valid causal inference in high-dimensional and complex settings
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The objective of this thesis is to consider some challenges that arise when conducting causal inference based on observational data. High dimensionality can occur when it is necessary to adjust for many covariates, and flexible models must be used to meet convergence assumptions. The latter may require the use of a novel machine learning estimator. Estimating nonparametrically-defined causal estimands at parametric rates and obtaining good-quality confidence intervals (with near nominal coverage) are the primary goals. Another challenge is providing a sensitivity analysis that can be applied in high-dimensional scenarios as a way of assessing the robustness of the results to missing confounders. Four papers are included in the thesis. A common theme in all the papers is covariate selection or nonparametric estimation of nuisance models. To provide insight into the performance of the approaches presented, some theoretical results are provided. Additionally, simulation studies are reported. In paper I, covariate selection is discussed as a method for removing redundant variables. This approach is compared to other strategies for variable selection that ensure reasonable confidence interval coverage. Paper II integrates variable selection into a sensitivity analysis, where the sensitivity parameter is the conditional correlation of the outcome and treatment variables. The validity of the analysis where the sensitivity parameter is small relative to the sample size is shown theoretically. In simulation settings, however, the analysis performs as expected, even for larger values of sensitivity parameters, when using a correction of the estimator of the residual variance for the outcome model. Paper IV extends the applicability of the sensitivity analysis method through the use of a different residual variance estimator and applies it to a real study of the effects of smoking during pregnancy on child birth weight. A real data problem of analysing the effect of early retirement on health outcomes is studied in Paper III. Rather than using variable selection strategies, convolutional neural networks are studied to fit the nuisance models.
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