How to deal with extreme propensity scores after IPTW

[Epi_Stats]

Hi,

I'm trying to run a propensity score analysis using proc psmatch and IPTW stabilized weights.

When I do this, there are a handful of observations with weighted propensity scores >1.

I can't share my full dataset, but here is a brief example of the matched IPTW data I have with 2 key confounders, the propensity scores (_PS_) and weighted propensity scores (PS_Weight)

data Matched_IPTW;
input ID AGE TREAT CFD1 CFD2 _PS_ PS_WEIGHT;
DATALINES;
1 83 1 1 2 0.95419 0.4235
2 69 1 1 2 0.94767 0.4264
3 71 1 1 0 0.06560 6.1600
4 83 1 1 1 0.05468 7.3904
5 71 1 1 1 0.04666 8.6598
6 76 0 1 1 0.93772 9.5675
7 70 1 1 0 0.04194 9.6356
8 69 0 1 2 0.95491 13.2150
9 76 1 0 1 0.02980 13.5610
10 68 1 0 0 0.01467 27.5379
;
RUN;

CFD1 is a binary confounder (1,0; yes/no), CFD2 is a categorical confounder (0,1,2; none/mild/moderate), _PS_ is the propensity score and PS_Weight is the stabilized PS generated from IPTW using SAS Proc psmatch and requesting WEIGHT=ATEWGT(STABILIZE=YES) in the assess statement.

In the SAS psmatch documentation, I can't find how to address extreme PS values that have been weighted - I have read that you can trim or truncate such values, but I don't know how to request this; or what method I should use to address this?

Any help would be really appreciated, please let me know if anything above is unclear etc.

Thank you in advance