Cervical cancer #1287
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Cervical cancer #1287
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…ses with proper structured manner as mixin, also remove unecessary input parameters other than self and person_id
…sed on other adult cancers
… the the chemo used
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per @mmsuarezcosta, this is now ready for review. |
thewati
reviewed
Jan 31, 2025
| .when(2, p['rr_hpv_vaccinated']), | ||
| Predictor('age_years', conditions_are_mutually_exclusive=True) | ||
| .when('.between(0,15)', 0.0) | ||
| .when('.between(50,110)', p['rr_hpv_age50plus']), |
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Is there a reason why this was reverted to .when('.between(50,110)', p['rr_hpv_age50plus']),? It was suggested to have it as .when('>50'),p['rr_hpv_age50plus']) earlier over here
thewati
reviewed
Jan 31, 2025
| # Current counts, total | ||
| out.update({ | ||
| f'total_{k}': v for k, v in df.loc[df.is_alive & (df['sex'] == 'F') & | ||
| (df['age_years'] > p['min_age_hpv'])].ce_hpv_cc_status.value_counts().items()}) |
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Suggested change
| (df['age_years'] > p['min_age_hpv'])].ce_hpv_cc_status.value_counts().items()}) | |
| df_alive_females = df.loc[df.is_alive & (df['sex'] == 'F') & (df['age_years'] > p['min_age_hpv'])] | |
| out.update({f'total_{k}': v for k, v in df_alive_females.ce_hpv_cc_status.value_counts().items()}) |
There is a repetition of this line of code here df.loc[df.is_alive & (df['sex'] == 'F') & (df['age_years'] > p['min_age_hpv'])] as well as at lines 1581 and 1586. Would probably be more efficient if these conditions are not repeated
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Here's a first draft of this module. I need to do another search to try to find additional data for calibration.
I couldn't upload the draft write as it was asking me to use the command line and Git LFS.