{"id":1557,"date":"2025-01-01T15:51:00","date_gmt":"2025-01-01T14:51:00","guid":{"rendered":"https:\/\/heva-data.com\/?p=1557"},"modified":"2025-07-04T15:51:44","modified_gmt":"2025-07-04T13:51:44","slug":"competing-risks","status":"publish","type":"post","link":"https:\/\/heva-data.com\/en\/competing-risks\/","title":{"rendered":"Competing Risks"},"content":{"rendered":"\n[et_pb_section fb_built=\u00a0\u00bb1&Prime; _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb background_enable_image=\u00a0\u00bboff\u00a0\u00bb custom_margin=\u00a0\u00bb||0px||false|false\u00a0\u00bb custom_padding=\u00a0\u00bb0px||||false|false\u00a0\u00bb locked=\u00a0\u00bboff\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb][et_pb_row column_structure=\u00a0\u00bb3_5,2_5&Prime; make_equal=\u00a0\u00bbon\u00a0\u00bb custom_padding_last_edited=\u00a0\u00bbon|phone\u00a0\u00bb _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb width_tablet=\u00a0\u00bb\u00a0\u00bb width_phone=\u00a0\u00bb90%\u00a0\u00bb width_last_edited=\u00a0\u00bbon|phone\u00a0\u00bb custom_margin_tablet=\u00a0\u00bb\u00a0\u00bb custom_margin_phone=\u00a0\u00bb||0px||false|false\u00a0\u00bb custom_margin_last_edited=\u00a0\u00bbon|phone\u00a0\u00bb custom_padding_tablet=\u00a0\u00bb\u00a0\u00bb custom_padding_phone=\u00a0\u00bb||0px||false|false\u00a0\u00bb hover_enabled=\u00a0\u00bb0&Prime; global_colors_info=\u00a0\u00bb{}\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime;][et_pb_column type=\u00a0\u00bb3_5&Prime; _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb global_colors_info=\u00a0\u00bb{}\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb][et_pb_text _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb text_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; text_font_size=\u00a0\u00bb24px\u00a0\u00bb header_2_font=\u00a0\u00bb|700|||||||\u00a0\u00bb header_2_text_align=\u00a0\u00bbcenter\u00a0\u00bb header_2_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; header_2_font_size=\u00a0\u00bb33px\u00a0\u00bb header_3_font=\u00a0\u00bb|700|||||||\u00a0\u00bb header_3_text_align=\u00a0\u00bbcenter\u00a0\u00bb header_3_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; header_3_font_size=\u00a0\u00bb24px\u00a0\u00bb text_orientation=\u00a0\u00bbcenter\u00a0\u00bb custom_margin=\u00a0\u00bb||||true|false\u00a0\u00bb custom_padding=\u00a0\u00bb||||true|false\u00a0\u00bb hover_enabled=\u00a0\u00bb0&Prime; custom_css_free_form=\u00a0\u00bbselector span{||  color:#1aa6a6;||}\u00a0\u00bb locked=\u00a0\u00bboff\u00a0\u00bb global_colors_info=\u00a0\u00bb{%22gcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2%22:%91%22text_text_color%22,%22header_2_text_color%22,%22header_3_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22header_3_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22header_3_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22header_3_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22header_3_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22header_3_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22header_3_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22header_3_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22header_3_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22header_3_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22header_3_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22header_3_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22header_3_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22header_3_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22header_3_text_color%22,%22text_text_color%22,%22header_2_text_color%22,%22header_3_text_color%22%93}\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime;]<h2 class=\"subtitle huik-text-title-3 huik-text-light\" style=\"text-align: left;\">Unmasking bias in your survival analysis<\/h2>[\/et_pb_text][et_pb_text _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb text_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; text_font_size=\u00a0\u00bb16px\u00a0\u00bb header_text_align=\u00a0\u00bbcenter\u00a0\u00bb module_alignment=\u00a0\u00bbcenter\u00a0\u00bb custom_padding=\u00a0\u00bb|0px||0px|false|true\u00a0\u00bb locked=\u00a0\u00bboff\u00a0\u00bb global_colors_info=\u00a0\u00bb{%22gcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2%22:%91%22text_text_color%22,%22text_text_color%22,%22text_text_color%22,%22text_text_color%22,%22text_text_color%22,%22text_text_color%22,%22text_text_color%22%93}\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb]<p style=\"font-weight: 400;\"><em>Competing risks methods are advanced statistical approaches designed to analyze multiple events that may simultaneously impact a patient, using methods such as cumulative incidence functions and Fine &amp; Gray models. These methods are essential in survival analysis, particularly in situations where multiple risks can interact and interfere with another, making traditional survival analyses potentially biased or incomplete.<\/em><\/p>[\/et_pb_text][\/et_pb_column][et_pb_column type=\u00a0\u00bb2_5&Prime; _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb background_color=\u00a0\u00bbgcid-c0e66333-91cf-44de-bb84-3ca29293711d\u00a0\u00bb background_enable_color=\u00a0\u00bboff\u00a0\u00bb background_image=\u00a0\u00bbhttps:\/\/heva-data.com\/wp-content\/uploads\/2025\/05\/working-together-on-project-happy-young-business-2025-03-13-23-04-23-utc-scaled.jpg\u00a0\u00bb custom_padding=\u00a0\u00bb10%||||false|false\u00a0\u00bb custom_padding_tablet=\u00a0\u00bb10%||||false|false\u00a0\u00bb custom_padding_phone=\u00a0\u00bb30%||||false|false\u00a0\u00bb custom_padding_last_edited=\u00a0\u00bbon|phone\u00a0\u00bb hover_enabled=\u00a0\u00bb0&Prime; custom_css_free_form=\u00a0\u00bbselector{||  border:3px solid white;||}\u00a0\u00bb border_radii=\u00a0\u00bbon|30px|30px|30px|30px\u00a0\u00bb global_colors_info=\u00a0\u00bb{%22gcid-c0e66333-91cf-44de-bb84-3ca29293711d%22:%91%22background_color%22%93,%22gcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2%22:%91%22background_color%22%93}\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime;][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb][et_pb_column _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb type=\u00a0\u00bb4_4&Prime; theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb][et_pb_text _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb text_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; text_font_size=\u00a0\u00bb16px\u00a0\u00bb custom_padding=\u00a0\u00bb|26px||0px|false|false\u00a0\u00bb locked=\u00a0\u00bboff\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime; header_3_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; header_3_font=\u00a0\u00bb|600|||||||\u00a0\u00bb global_colors_info=\u00a0\u00bb{%22gcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2%22:%91%22text_text_color%22,%22header_3_text_color%22,%22text_text_color%22,%22header_3_text_color%22,%22text_text_color%22%93}\u00a0\u00bb custom_margin=\u00a0\u00bb60px||||false|false\u00a0\u00bb]<h3>Survival analysis\u00a0<\/h3>\n<p>Survival analysis encompasses a wide range of statistical methods designed to handle censored data. Censoring occurs when we can only partially observe the timing of an event \u2013 we know that a subject hasn&rsquo;t experienced the event (such as death, system failure, or disease recurrence) up until a certain date, but we lose track of them after that point. These analyses allow for the inclusion of incomplete information in the analysis, enabling researchers to estimate survival probabilities and time-to-event outcomes more accurately.<\/p>\n<p style=\"font-weight: 400;\"><\/p>[\/et_pb_text][et_pb_image src=\u00a0\u00bbhttps:\/\/heva-data.com\/wp-content\/uploads\/2025\/06\/img-0001.png\u00a0\u00bb _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb title_text=\u00a0\u00bbimg-0001&Prime; hover_enabled=\u00a0\u00bb0&Prime; sticky_enabled=\u00a0\u00bb0&Prime;][\/et_pb_image][et_pb_text _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb text_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; text_font_size=\u00a0\u00bb16px\u00a0\u00bb custom_padding=\u00a0\u00bb|26px||0px|false|false\u00a0\u00bb hover_enabled=\u00a0\u00bb0&Prime; locked=\u00a0\u00bboff\u00a0\u00bb global_colors_info=\u00a0\u00bb{%22gcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2%22:%91%22text_text_color%22%93}\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime;]In a survival analysis, we have two informations at our disposal:\n<ul>\n\t<li>the presence or absence of the event of interest,<\/li>\n\t<li>the time to event for patients having the event of interest or time to censoring for patients without the event of interest.<\/li>\n<\/ul>\n\n\nThe Kaplan-Meier estimator is the most common method in survival analysis. It estimates the survival probability past any given time point while accounting for censored observations. It provides a step-by-step estimate of the survival function based on observed event times.\n\n<p style=\"font-weight: 400;\">[\/et_pb_text][et_pb_image src=\u00a0\u00bbhttps:\/\/heva-data.com\/wp-content\/uploads\/2025\/06\/img-0002.png\u00a0\u00bb _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb title_text=\u00a0\u00bbimg-0002&Prime; hover_enabled=\u00a0\u00bb0&Prime; sticky_enabled=\u00a0\u00bb0&Prime;][\/et_pb_image][et_pb_text _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb text_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; text_font_size=\u00a0\u00bb16px\u00a0\u00bb custom_padding=\u00a0\u00bb|26px||0px|false|false\u00a0\u00bb hover_enabled=\u00a0\u00bb0&Prime; locked=\u00a0\u00bboff\u00a0\u00bb global_colors_info=\u00a0\u00bb{%22gcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2%22:%91%22text_text_color%22,%22header_3_text_color%22%93}\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime; header_3_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; header_3_font=\u00a0\u00bb|600|||||||\u00a0\u00bb custom_margin=\u00a0\u00bb60px||||false|false\u00a0\u00bb]<h3>What is a competing risk?<\/h3>\n\n[\/et_pb_text][et_pb_image src=\u00a0\u00bbhttps:\/\/heva-data.com\/wp-content\/uploads\/2025\/06\/img-3.png\u00a0\u00bb _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb title_text=\u00a0\u00bbimg-3&Prime; hover_enabled=\u00a0\u00bb0&Prime; sticky_enabled=\u00a0\u00bb0&Prime;][\/et_pb_image][et_pb_text _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb text_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; text_font_size=\u00a0\u00bb16px\u00a0\u00bb custom_padding=\u00a0\u00bb|26px||0px|false|false\u00a0\u00bb hover_enabled=\u00a0\u00bb0&Prime; locked=\u00a0\u00bboff\u00a0\u00bb global_colors_info=\u00a0\u00bb{%22gcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2%22:%91%22text_text_color%22%93}\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime;]<p><span>A competing risk is an event that can occur in place of the event of interest, thereby preventing its occurrence or accurate observation. For instance, if a patient dies prior to being hospitalized, the hospitalization event is no longer observable.<\/span><\/p>\n<p style=\"font-weight: 400;\"><\/p>[\/et_pb_text][et_pb_text _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb text_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; text_font_size=\u00a0\u00bb16px\u00a0\u00bb custom_padding=\u00a0\u00bb|26px||0px|false|false\u00a0\u00bb hover_enabled=\u00a0\u00bb0&Prime; locked=\u00a0\u00bboff\u00a0\u00bb global_colors_info=\u00a0\u00bb{%22gcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2%22:%91%22text_text_color%22,%22header_3_text_color%22%93}\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime; header_3_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; header_3_font=\u00a0\u00bb|600|||||||\u00a0\u00bb custom_margin=\u00a0\u00bb60px||||false|false\u00a0\u00bb]<h3>How competing risks can bias your analysis and strategy for addressing them<\/h3>\n<p>The assumption underlying traditional survival analysis is that censored patients are presumed to have the same risk profile as those who remain under observation. This means that, despite being censored\u2014either due to loss to follow-up, withdrawal, or the end of the study period\u2014these patients are treated as if they would have experienced the event of interest had they continued to be monitored. However, in the context of competing risks, this assumption becomes problematic. If a competing event occurs before the event of interest, it nullifies the risk of the event of interest for that patient, reducing its probability of occurrence to zero. This is because the competing event precludes the possibility of the event of interest happening, a phenomenon that conventional survival analysis methods fail to address.\n\n<\/p>\n\n[\/et_pb_text][et_pb_image src=\u00a0\u00bbhttps:\/\/heva-data.com\/wp-content\/uploads\/2025\/06\/img-4.png\u00a0\u00bb _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb title_text=\u00a0\u00bbimg-4&Prime; hover_enabled=\u00a0\u00bb0&Prime; sticky_enabled=\u00a0\u00bb0&Prime;][\/et_pb_image][et_pb_text _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb text_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; text_font_size=\u00a0\u00bb16px\u00a0\u00bb custom_padding=\u00a0\u00bb|26px||0px|false|false\u00a0\u00bb hover_enabled=\u00a0\u00bb0&Prime; locked=\u00a0\u00bboff\u00a0\u00bb global_colors_info=\u00a0\u00bb{%22gcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2%22:%91%22text_text_color%22,%22header_3_text_color%22%93}\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime; header_3_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; header_3_font=\u00a0\u00bb|600|||||||\u00a0\u00bb custom_margin=\u00a0\u00bb60px||||false|false\u00a0\u00bb]<p>To account for competing events, a virtual risk set should be created that includes patients actually at risk of the event of interest but also patients who have experienced a competing event, effectively reflecting that their risk of having the primary event is zero. While this modified risk set may no longer be directly interpretable, it allows for a direct translation into the cumulative incidence rate of the event of interest.<\/p>\n<p>Heva studied the potential impact of neglecting competing events in survival analysis (<a href=\"https:\/\/static.hevaweb.com\/web\/PDF\/ef229740e8036-ignoring-competing-event-in-survival-analyses-the-amplitude-of-the-bias-in-kaplan-meier-estimates-assessed-through-simulations.pdf\" target=\"_blank\" rel=\"noopener\">see the poster<\/a>). The findings demonstrated that ignoring competing risks leads to systematic bias in results. This bias becomes more pronounced under two key conditions:<\/p>\n<ul>\n<li>when competing events occur more frequently,<\/li>\n<li>when the follow-up period extends longer.<\/li>\n<\/ul>\n<p>&nbsp;<\/p>[\/et_pb_text][et_pb_image src=\u00a0\u00bbhttps:\/\/heva-data.com\/wp-content\/uploads\/2025\/06\/img-000005.png\u00a0\u00bb _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb title_text=\u00a0\u00bbimg-000005&Prime; hover_enabled=\u00a0\u00bb0&Prime; sticky_enabled=\u00a0\u00bb0&Prime;][\/et_pb_image][et_pb_text _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb text_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; text_font_size=\u00a0\u00bb16px\u00a0\u00bb custom_padding=\u00a0\u00bb|26px|0px|0px|false|false\u00a0\u00bb hover_enabled=\u00a0\u00bb0&Prime; locked=\u00a0\u00bboff\u00a0\u00bb global_colors_info=\u00a0\u00bb{%22gcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2%22:%91%22text_text_color%22,%22header_3_text_color%22%93}\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime; header_3_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; header_3_font=\u00a0\u00bb|600|||||||\u00a0\u00bb custom_margin=\u00a0\u00bb60px||0px||false|false\u00a0\u00bb]<h3>Applications of competing risk analyses<\/h3>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb column_structure=\u00a0\u00bb1_2,1_2&Prime; hover_enabled=\u00a0\u00bb0&Prime; sticky_enabled=\u00a0\u00bb0&Prime; make_equal=\u00a0\u00bbon\u00a0\u00bb][et_pb_column _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb type=\u00a0\u00bb1_2&Prime; theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb custom_padding=\u00a0\u00bb50px|50px|50px|50px|false|false\u00a0\u00bb custom_padding_tablet=\u00a0\u00bb50px|50px|50px|50px|false|false\u00a0\u00bb custom_padding_phone=\u00a0\u00bb30px|10px|30px|10px|false|false\u00a0\u00bb custom_padding_last_edited=\u00a0\u00bbon|phone\u00a0\u00bb custom_css_free_form=\u00a0\u00bbselector{||    position: relative;||    z-index: 1; \/* S&rsquo;assurer que le texte est au-dessus *\/||    background-color: rgba(221, 242, 242, 0.95); \/* Turquoise tram\u00e9 \u00e0 15% *\/||    opacity: 1; \/* Effet de transparence \u00e0 95% *\/||    color: #000; \/* Couleur du texte, \u00e0 ajuster si n\u00e9cessaire *\/||  backdrop-filter: blur(5px);||  -webkit-backdrop-filter: blur(5px);||}\u00a0\u00bb border_radii=\u00a0\u00bbon|30px|30px|30px|30px\u00a0\u00bb][et_pb_text _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb text_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; text_font_size=\u00a0\u00bb16px\u00a0\u00bb custom_padding=\u00a0\u00bb|26px||0px|false|false\u00a0\u00bb hover_enabled=\u00a0\u00bb0&Prime; locked=\u00a0\u00bboff\u00a0\u00bb global_colors_info=\u00a0\u00bb{%22gcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2%22:%91%22text_text_color%22,%22header_4_text_color%22,%22header_5_text_color%22%93}\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb header_4_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; header_4_font=\u00a0\u00bb|700|||||||\u00a0\u00bb header_4_line_height=\u00a0\u00bb1.3em\u00a0\u00bb header_5_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; header_5_font=\u00a0\u00bb|700|||||||\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime; custom_margin=\u00a0\u00bb||5px||false|false\u00a0\u00bb]<h4>Treatment discontinuation<\/h4>\n<p>Treatment discontinuation is a classic competing risks scenario, as patients may stop treatment for various reasons: experiencing adverse effects, failing to adhere to the treatment i.e. non-adherence, dying before treatment completion, or achieving their therapeutic goals (e.g. clinical remission or desired treatment outcome).<\/p>\n<p>&nbsp;<\/p>\n<h5>\u2753Research questions<\/h5>\n<ul>\n<li>What is the rate of treatment discontinuation due to death or treatment switch?<\/li>\n<li>What is the impact of patient characteristics on treatment discontinuation ?<\/li>\n<\/ul>\n<h5>????\u00a0Event of interest<\/h5>\n<ul>\n<li>Treatment switch<\/li>\n<\/ul>\n<h5>\u26a0\ufe0f\u00a0Competing event<\/h5>\n<ul>\n<li>Treatment discontinuation for others reasons (death, adverse event)<\/li>\n<\/ul>[\/et_pb_text][et_pb_image src=\u00a0\u00bbhttps:\/\/heva-data.com\/wp-content\/uploads\/2025\/06\/img-000006.png\u00a0\u00bb _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb title_text=\u00a0\u00bbimg-000006&Prime; hover_enabled=\u00a0\u00bb0&Prime; sticky_enabled=\u00a0\u00bb0&Prime;][\/et_pb_image][\/et_pb_column][et_pb_column _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb type=\u00a0\u00bb1_2&Prime; theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb custom_padding=\u00a0\u00bb50px|50px|50px|50px|false|false\u00a0\u00bb custom_padding_tablet=\u00a0\u00bb50px|50px|50px|50px|false|false\u00a0\u00bb custom_padding_phone=\u00a0\u00bb30px|10px|30px|10px|false|false\u00a0\u00bb custom_padding_last_edited=\u00a0\u00bbon|phone\u00a0\u00bb custom_css_free_form=\u00a0\u00bbselector{||    position: relative;||    z-index: 1; \/* S&rsquo;assurer que le texte est au-dessus *\/||    background-color: rgba(221, 242, 242, 0.95); \/* Turquoise tram\u00e9 \u00e0 15% *\/||    opacity: 1; \/* Effet de transparence \u00e0 95% *\/||    color: #000; \/* Couleur du texte, \u00e0 ajuster si n\u00e9cessaire *\/||  backdrop-filter: blur(5px);||  -webkit-backdrop-filter: blur(5px);||}\u00a0\u00bb border_radii=\u00a0\u00bbon|30px|30px|30px|30px\u00a0\u00bb][et_pb_text _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb text_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; text_font_size=\u00a0\u00bb16px\u00a0\u00bb custom_padding=\u00a0\u00bb|26px||0px|false|false\u00a0\u00bb locked=\u00a0\u00bboff\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb header_4_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; header_4_font=\u00a0\u00bb|700|||||||\u00a0\u00bb header_4_line_height=\u00a0\u00bb1.3em\u00a0\u00bb header_5_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; header_5_font=\u00a0\u00bb|700|||||||\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime; global_colors_info=\u00a0\u00bb{%22gcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2%22:%91%22text_text_color%22,%22header_4_text_color%22,%22header_5_text_color%22,%22text_text_color%22,%22header_4_text_color%22,%22header_5_text_color%22%93}\u00a0\u00bb custom_margin=\u00a0\u00bb||5px||false|false\u00a0\u00bb]<h4>Clinical events<\/h4>\n<p>A specific type of competing risk scenario, known as a semi-competing risk situation, arises when the occurrence of death precludes the occurrence of the clinical event of interest, while the reverse is not true. The clinical event of interest could involve the occurrence of adverse events, disease progression, or treatment failure.<\/p>\n<p>&nbsp;<\/p>\n<h5>\u2753Research questions<\/h5>\n<ul>\n<li>What is the rate of rehospitalizations following initial surgery?<\/li>\n<li>What is the impact of the surgical method on rehospitalization rates?<\/li>\n<\/ul>\n<h5>????\u00a0Event of interest<\/h5>\n<ul>\n<li>Rehospitalization<\/li>\n<\/ul>\n<h5>\u26a0\ufe0f\u00a0Competing event<\/h5>\n<ul>\n<li>Death prior to rehospitalization<\/li>\n<\/ul>\n<ul><\/ul>[\/et_pb_text][et_pb_image src=\u00a0\u00bbhttps:\/\/heva-data.com\/wp-content\/uploads\/2025\/06\/img-00000000007.png\u00a0\u00bb _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb title_text=\u00a0\u00bbimg-00000000007&Prime; hover_enabled=\u00a0\u00bb0&Prime; sticky_enabled=\u00a0\u00bb0&Prime; locked=\u00a0\u00bboff\u00a0\u00bb][\/et_pb_image][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb][et_pb_column _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb type=\u00a0\u00bb4_4&Prime; theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb][et_pb_text _builder_version=\u00a0\u00bb4.24.2&Prime; _module_preset=\u00a0\u00bbdefault\u00a0\u00bb text_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; text_font_size=\u00a0\u00bb16px\u00a0\u00bb custom_padding=\u00a0\u00bb|26px||0px|false|false\u00a0\u00bb hover_enabled=\u00a0\u00bb0&Prime; locked=\u00a0\u00bboff\u00a0\u00bb global_colors_info=\u00a0\u00bb{%22gcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2%22:%91%22text_text_color%22,%22header_3_text_color%22%93}\u00a0\u00bb theme_builder_area=\u00a0\u00bbpost_content\u00a0\u00bb sticky_enabled=\u00a0\u00bb0&Prime; header_3_text_color=\u00a0\u00bbgcid-07fd6007-ae25-4e13-bbf0-52acc155a8b2&Prime; header_3_font=\u00a0\u00bb|600|||||||\u00a0\u00bb custom_margin=\u00a0\u00bb60px||||false|false\u00a0\u00bb]<h3>Conclusion<\/h3>\n<div class=\"conclusion\"><em>In conclusion, understanding and accurately modeling competing risks is fundemental to conducting valid survival analyses and for obtaining reliable and meaningful results. Whether in clinical trials, epidemiological studies, or medical research, failure to account for events that may interfere with the occurrence of the primary outcome of interest can significantly impact their interpretation. Understanding the interplay between competing events not only ensures statistical rigor but also provides clinicians with more reliable evidence for patient care.<\/em><\/div>\n<p>&nbsp;<\/p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]\n","protected":false},"excerpt":{"rendered":"<p>Unmasking bias in your survival analysisCompeting risks methods are advanced statistical approaches designed to analyze multiple events that may simultaneously impact a patient, using methods such as cumulative incidence functions and Fine &amp; Gray models. These methods are essential in survival analysis, particularly in situations where multiple risks can interact and interfere with another, making [&hellip;]<\/p>\n","protected":false},"author":6,"featured_media":1559,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","_crdt_document":"","advanced_seo_description":"","jetpack_seo_html_title":"","jetpack_seo_noindex":false,"footnotes":""},"categories":[8],"tags":[],"class_list":["post-1557","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-methodes-et-stats"],"jetpack_featured_media_url":"https:\/\/heva-data.com\/wp-content\/uploads\/2025\/06\/b926565f09976-img-0-scaled.png","jetpack_shortlink":"https:\/\/wp.me\/pgrg3B-p7","_links":{"self":[{"href":"https:\/\/heva-data.com\/en\/wp-json\/wp\/v2\/posts\/1557","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/heva-data.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/heva-data.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/heva-data.com\/en\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/heva-data.com\/en\/wp-json\/wp\/v2\/comments?post=1557"}],"version-history":[{"count":6,"href":"https:\/\/heva-data.com\/en\/wp-json\/wp\/v2\/posts\/1557\/revisions"}],"predecessor-version":[{"id":1576,"href":"https:\/\/heva-data.com\/en\/wp-json\/wp\/v2\/posts\/1557\/revisions\/1576"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/heva-data.com\/en\/wp-json\/wp\/v2\/media\/1559"}],"wp:attachment":[{"href":"https:\/\/heva-data.com\/en\/wp-json\/wp\/v2\/media?parent=1557"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/heva-data.com\/en\/wp-json\/wp\/v2\/categories?post=1557"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/heva-data.com\/en\/wp-json\/wp\/v2\/tags?post=1557"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}